diff --git "a/logs/title_pilot_train.log" "b/logs/title_pilot_train.log"
new file mode 100644--- /dev/null
+++ "b/logs/title_pilot_train.log"
@@ -0,0 +1,672 @@
+=== Pilot Title LoRA started at Thu Jun 18 08:56:40 UTC 2026 ===
+[INFO|2026-06-18 08:56:45] llamafactory.hparams.parser:523 >> Process rank: 0, world size: 1, device: cuda:0, distributed training: False, compute dtype: torch.bfloat16
+[INFO|tokenization_utils_base.py:2068] 2026-06-18 08:56:46,117 >> loading file tokenizer.model from cache at /root/.cache/huggingface/hub/models--YoLo2000--TiLamb-7B/snapshots/9e9426a248492fd02abfbd21d13f000456408bde/tokenizer.model
+[INFO|tokenization_utils_base.py:2068] 2026-06-18 08:56:46,117 >> loading file tokenizer.json from cache at /root/.cache/huggingface/hub/models--YoLo2000--TiLamb-7B/snapshots/9e9426a248492fd02abfbd21d13f000456408bde/tokenizer.json
+[INFO|tokenization_utils_base.py:2068] 2026-06-18 08:56:46,117 >> loading file added_tokens.json from cache at None
+[INFO|tokenization_utils_base.py:2068] 2026-06-18 08:56:46,117 >> loading file special_tokens_map.json from cache at /root/.cache/huggingface/hub/models--YoLo2000--TiLamb-7B/snapshots/9e9426a248492fd02abfbd21d13f000456408bde/special_tokens_map.json
+[INFO|tokenization_utils_base.py:2068] 2026-06-18 08:56:46,117 >> loading file tokenizer_config.json from cache at /root/.cache/huggingface/hub/models--YoLo2000--TiLamb-7B/snapshots/9e9426a248492fd02abfbd21d13f000456408bde/tokenizer_config.json
+[INFO|tokenization_utils_base.py:2068] 2026-06-18 08:56:46,117 >> loading file chat_template.jinja from cache at None
+[INFO|configuration_utils.py:765] 2026-06-18 08:56:47,107 >> loading configuration file config.json from cache at /root/.cache/huggingface/hub/models--YoLo2000--TiLamb-7B/snapshots/9e9426a248492fd02abfbd21d13f000456408bde/config.json
+[INFO|configuration_utils.py:839] 2026-06-18 08:56:47,109 >> Model config LlamaConfig {
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": 1,
+  "dtype": "float16",
+  "eos_token_id": 2,
+  "head_dim": 128,
+  "hidden_act": "silu",
+  "hidden_size": 4096,
+  "initializer_range": 0.02,
+  "intermediate_size": 11008,
+  "max_position_embeddings": 4096,
+  "mlp_bias": false,
+  "model_type": "llama",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 32,
+  "num_key_value_heads": 32,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-05,
+  "rope_scaling": null,
+  "rope_theta": 10000.0,
+  "tie_word_embeddings": false,
+  "transformers_version": "4.56.2",
+  "use_cache": true,
+  "vocab_size": 61221
+}
+
+[INFO|tokenization_utils_base.py:2068] 2026-06-18 08:56:47,383 >> loading file tokenizer.model from cache at /root/.cache/huggingface/hub/models--YoLo2000--TiLamb-7B/snapshots/9e9426a248492fd02abfbd21d13f000456408bde/tokenizer.model
+[INFO|tokenization_utils_base.py:2068] 2026-06-18 08:56:47,383 >> loading file tokenizer.json from cache at /root/.cache/huggingface/hub/models--YoLo2000--TiLamb-7B/snapshots/9e9426a248492fd02abfbd21d13f000456408bde/tokenizer.json
+[INFO|tokenization_utils_base.py:2068] 2026-06-18 08:56:47,383 >> loading file added_tokens.json from cache at None
+[INFO|tokenization_utils_base.py:2068] 2026-06-18 08:56:47,383 >> loading file special_tokens_map.json from cache at /root/.cache/huggingface/hub/models--YoLo2000--TiLamb-7B/snapshots/9e9426a248492fd02abfbd21d13f000456408bde/special_tokens_map.json
+[INFO|tokenization_utils_base.py:2068] 2026-06-18 08:56:47,383 >> loading file tokenizer_config.json from cache at /root/.cache/huggingface/hub/models--YoLo2000--TiLamb-7B/snapshots/9e9426a248492fd02abfbd21d13f000456408bde/tokenizer_config.json
+[INFO|tokenization_utils_base.py:2068] 2026-06-18 08:56:47,383 >> loading file chat_template.jinja from cache at None
+[INFO|2026-06-18 08:56:47] llamafactory.data.template:144 >> Add pad token: </s>
+[INFO|2026-06-18 08:56:47] llamafactory.data.loader:144 >> Loading dataset tibetan_title_sft_pilot/train.jsonl...
+Setting num_proc from 8 back to 1 for the train split to disable multiprocessing as it only contains one shard.
+
Generating train split: 0 examples [00:00, ? examples/s]
Generating train split: 1550 examples [00:00, 10465.22 examples/s]
Generating train split: 3649 examples [00:00, 14119.86 examples/s]
Generating train split: 5684 examples [00:00, 15782.09 examples/s]
Generating train split: 6035 examples [00:00, 14658.37 examples/s]
+
Converting format of dataset (num_proc=8):   0%|          | 0/6035 [00:00<?, ? examples/s]
Converting format of dataset (num_proc=8):   9%|▉         | 561/6035 [00:00<00:01, 2918.82 examples/s]
Converting format of dataset (num_proc=8):  90%|████████▉ | 5411/6035 [00:00<00:00, 21599.77 examples/s]
Converting format of dataset (num_proc=8): 100%|██████████| 6035/6035 [00:00<00:00, 13579.49 examples/s]
+[INFO|2026-06-18 08:56:48] llamafactory.data.loader:144 >> Loading dataset tibetan_title_sft_pilot/val.jsonl...
+Setting num_proc from 8 back to 1 for the train split to disable multiprocessing as it only contains one shard.
+
Generating train split: 0 examples [00:00, ? examples/s]
Generating train split: 100 examples [00:00, 10279.15 examples/s]
+
Converting format of dataset (num_proc=8):   0%|          | 0/100 [00:00<?, ? examples/s]
Converting format of dataset (num_proc=8):  13%|█▎        | 13/100 [00:00<00:00, 88.00 examples/s]
Converting format of dataset (num_proc=8): 100%|██████████| 100/100 [00:00<00:00, 314.64 examples/s]
+
Running tokenizer on dataset (num_proc=8):   0%|          | 0/6035 [00:00<?, ? examples/s]
Running tokenizer on dataset (num_proc=8):  13%|█▎        | 755/6035 [00:02<00:20, 263.06 examples/s]
Running tokenizer on dataset (num_proc=8):  50%|█████     | 3018/6035 [00:03<00:02, 1292.65 examples/s]
Running tokenizer on dataset (num_proc=8):  75%|███████▌  | 4527/6035 [00:03<00:00, 2095.01 examples/s]
Running tokenizer on dataset (num_proc=8): 100%|██████████| 6035/6035 [00:03<00:00, 2878.99 examples/s]
Running tokenizer on dataset (num_proc=8): 100%|██████████| 6035/6035 [00:03<00:00, 1707.27 examples/s]
+training example:
+input_ids:
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31034, 32013, 38440, 35305, 37078, 32764, 34579, 32009, 13, 41754, 32354, 36925, 33108, 48900, 37199, 36113, 35305, 32161, 32742, 32000, 13, 32278, 36095, 32160, 32013, 34504, 36927, 33166, 13, 30410, 30410, 478, 13, 37183, 32060, 39898, 31401, 32069, 39611, 13, 42164, 31326, 32009, 32445, 13, 33631, 32000, 13, 49137, 32325, 33151, 31601, 32208, 32354, 36518, 31601, 31326, 32007, 42379, 40586, 29871, 32004, 33631, 13, 33801, 38859, 32471, 32307, 42520, 31034, 32009, 33629, 33435, 32826, 227, 191, 143, 32000, 13, 36095, 34741, 34504, 49730, 40623, 32325, 13, 35863, 34744, 47541, 31344, 37199, 32415, 35931, 33052, 13, 40277, 61215, 31401, 33354, 32033, 42379, 34107, 30410, 30015, 31643, 32028, 13, 31208, 32019, 49023, 34579, 32009, 33331, 30410, 13, 32185, 33072, 29871, 30410, 34728, 35351, 33162, 31401, 13, 31034, 29871, 30410, 33984, 34107, 33166, 32085, 46554, 39852, 13, 34243, 32742, 32000, 13, 31232, 41442, 38171, 33160, 32054, 31208, 33120, 32009, 31208, 34421, 30410, 13, 37128, 32009, 33631, 32000, 13, 31326, 31104, 32975, 31344, 32459, 32013, 49358, 35461, 40907, 13, 31034, 46481, 32009, 32459, 33813, 42759, 31614, 32160, 34050, 33216, 33247, 31401, 29914, 13, 39056, 55114, 33116, 32142, 32000, 13, 31326, 32132, 43488, 32119, 50715, 30410, 13, 32278, 39439, 36067, 32256, 32164, 33047, 30410, 32016, 32199, 35874, 34360, 30410, 13, 31034, 32009, 44807, 32093, 32672, 43152, 32024, 43099, 30410, 13, 32459, 30410, 32366, 32013, 32009, 32009, 13, 35933, 36856, 32354, 32278, 36095, 32017, 32060, 13, 37609, 32013, 41991, 32664, 58367, 32013, 32278, 43803, 38886, 32306, 35234, 13, 31034, 31896, 32742, 32000, 13, 34336, 41313, 34504, 39743, 35240, 32019, 30410, 30410, 30410, 32164, 32009, 13, 44704, 31614, 32164, 32348, 31208, 32160, 32003, 42164, 31326, 36224, 31601, 32160, 32013, 13, 31034, 41442, 31104, 51974, 39898, 32009, 34906, 31232, 227, 191, 143, 32000, 13, 32278, 36095, 33825, 32160, 30410, 32009, 13, 31208, 56435, 32354, 32009, 39108, 32278, 38974, 31208, 29871, 30410, 33083, 38776, 29871, 32371, 34369, 34728, 13, 32715, 34165, 36864, 32664, 39092, 32975, 54324, 32119, 32017, 32009, 13, 29893, 13, 32445, 34906, 31232, 32000, 13, 35451, 32248, 13, 33001, 37735, 38886, 31104, 32160, 36110, 31401, 32180, 39909, 32039, 33072, 37861, 32415, 32764, 33172, 32278, 30410, 13, 44872, 29871, 30410, 32009, 29871, 30410, 29871, 31034, 29871, 30410, 29871, 38171, 29871, 32737, 32003, 37753, 31326, 32009, 41225, 13, 51706, 32387, 32119, 52737, 13, 32459, 32305, 32000, 13, 39092, 42384, 32949, 32013, 33257, 30410, 49265, 56435, 32354, 13, 32278, 39108, 33984, 47607, 38941, 32155, 32017, 32009, 49535, 30410, 13, 31326, 33046, 42460, 60373, 31104, 35351, 32272, 36730, 32491, 37507, 38886, 30410, 13, 38886, 31104, 41010, 32155, 32017, 32009, 49084, 32000, 13, 32278, 36095, 33120, 32013, 34504, 32093, 33047, 32278, 33448, 43529, 33116, 39204, 30410, 13, 49137, 32009, 36410, 37732, 32941, 31232, 61215, 31644, 32009, 13, 49137, 32033, 32543, 45196, 38033, 31326, 32160, 31344, 32119, 32348, 30410, 13, 13, 32009, 31232, 41442, 45047, 31208, 35420, 32012, 13, 45256, 50017, 39741, 29871, 32000, 29871, 32000, 34304, 37583, 31601, 32039, 31034, 38981, 31896, 30410, 32205, 35141, 30410, 13, 32278, 36095, 30410, 32327, 32013, 34504, 49730, 56435, 32028, 13, 32009, 36095, 49265, 37583, 32009, 32878, 33287, 35461, 38886, 30410, 13, 31034, 32003, 48843, 36278, 32257, 227, 191, 143, 32000, 29871, 32009, 37885, 35085, 31034, 31401, 13, 45636, 32016, 31344, 32579, 45196, 31601, 32975, 13, 36002, 32975, 31344, 32459, 32013, 34504, 33039, 32354, 32551, 32800, 33108, 37463, 31601, 32009, 13, 50796, 33313, 33984, 50414, 31208, 38690, 34716, 29901, 32554, 32013, 34906, 31601, 32354, 13, 39800, 37656, 33523, 29871, 59352, 32013, 32272, 32009, 13, 35874, 32055, 35399, 32164, 45255, 32205, 33313, 33631, 227, 191, 143, 32000, 29871, 32000, 33985, 32009, 39813, 13, 31643, 32579, 44806, 31104, 32318, 45929, 49793, 32038, 33257, 32007, 32013, 32278, 33011, 35305, 13, 36095, 53556, 33115, 34537, 49730, 56435, 32000, 13, 31344, 39108, 42422, 32009, 35416, 32664, 30410, 32056, 32119, 35270, 31401, 227, 191, 143, 13, 34504, 32742, 32002, 49067, 31896, 31601, 30410, 32009, 31208, 37128, 31601, 33115, 32142, 41442, 37849, 13, 32551, 32164, 42379, 31601, 32201, 32000, 13, 31104, 32975, 13, 35482, 34899, 31601, 33039, 32240, 32551, 34027, 33108, 58602, 32325, 13, 34243, 33313, 31208, 32013, 32272, 32009, 32092, 29912, 39741, 29871, 32032, 32208, 30410, 13, 31208, 32013, 40974, 32014, 36949, 32013, 32272, 34733, 13, 36091, 32975, 40123, 34504, 30410, 45290, 35312, 32325, 13, 32009, 39108, 32278, 37349, 32009, 40980, 32318, 32611, 32445, 33184, 31644, 32009, 36410, 45461, 29905, 13, 31034, 31401, 32554, 32013, 29871, 32000, 41817, 33313, 55768, 32013, 40214, 38131, 32727, 43617, 29871, 37530, 29892, 40969, 32746, 36244, 38131, 33166, 32746, 13, 35353, 38538, 32975, 39037, 32000, 13, 34835, 31104, 30410, 35461, 34504, 30410, 32009, 32003, 32551, 34027, 33108, 35628, 33509, 49793, 33313, 13, 32272, 48234, 32325, 32272, 32039, 36410, 32889, 39741, 45104, 36927, 35351, 13, 32136, 31104, 32009, 32383, 32120, 32579, 45196, 31896, 31601, 32013, 32272, 31643, 32000, 13, 36013, 35551, 31344, 32203, 49265, 56435, 32354, 13, 32242, 32198, 35482, 32009, 48510, 32180, 35681, 36316, 32325, 13, 32278, 37539, 36878, 32016, 33052, 32354, 33072, 39697, 32354, 13, 31326, 33631, 31601, 32325, 41754, 46027, 227, 191, 143, 32000, 13, 32318, 30410, 32203, 13, 35863, 35551, 32003, 31034, 32004, 33801, 32987, 53247, 32551, 35356, 31614, 32146, 32208, 32005, 13, 32949, 31344, 35520, 35353, 32206, 33115, 32327, 32013, 13, 31034, 41442, 31601, 32498, 48165, 32013, 32272, 31034, 32000, 13, 32278, 36095, 38008, 49730, 35312, 31208, 32203, 13, 33255, 33984, 37583, 30410, 34537, 29871, 30410, 33984, 37362, 29871, 32000, 29871, 30410, 33984, 31896, 31452, 33509, 31896, 31601, 29871, 32136, 29871, 30410, 13, 34504, 40847, 32009, 32715, 41835, 32080, 31896, 31452, 40847, 32975, 38957, 227, 191, 143, 32000, 13, 32278, 36095, 35461, 31034, 51041, 33801, 36095, 32000, 32664, 32013, 29871, 30410, 33072, 30410, 29871, 30410, 38518, 29871, 30410, 13, 50796, 33313, 32272, 32009, 31232, 61215, 31644, 33984, 31452, 32206, 29871, 30410, 33184, 32013, 32272, 31643, 34660, 13, 34545, 32278, 39949, 31601, 35765, 49067, 47481, 32011, 13, 34441, 40784, 32088, 49730, 32379, 32164, 13, 32554, 35812, 33664, 32003, 34509, 38319, 13, 31643, 42578, 32548, 36598, 33695, 33257, 32742, 227, 191, 143, 32000, 13, 32278, 31344, 37199, 32230, 35600, 32033, 32497, 32000, 13, 35416, 32009, 33257, 33313, 32382, 32137, 32000, 30410, 13, 33108, 13, 49137, 32055, 35399, 33014, 30410, 33563, 32205, 32013, 39909, 32354, 13, 31643, 32889, 31104, 32325, 32278, 34089, 32038, 38440, 31344, 32205, 51358, 227, 191, 143, 32000, 13, 41754, 31104, 32975, 31344, 32459, 32013, 34504, 49730, 35312, 35883, 13, 227, 173, 184, 227, 174, 131, 227, 173, 179, 227, 174, 144, 227, 173, 178, 227, 173, 184, 227, 173, 167, 227, 174, 131, 29871, 227, 173, 176, 227, 174, 142, 227, 173, 177, 13, 32278, 48284, 39542, 32009, 45290, 34179, 31208, 35688, 31401, 32158, 30410, 13, 36095, 34908, 34537, 49730, 30410, 13, 32278, 32382, 33905, 31344, 32155, 32017, 32009, 36810, 13, 44844, 31104, 33523, 33257, 39741, 30410, 13, 34322, 32248, 13, 40277, 33115, 33354, 32122, 32611, 13, 32303, 31896, 37199, 42942, 32742, 32000, 13, 30410, 30410, 30410, 32561, 34884, 52585, 30410, 30410, 13, 32459, 32007, 61215, 31401, 33354, 32004, 13, 35933, 36351, 36232, 29871, 32975, 32158, 30410, 32975, 13, 33894, 38544, 34089, 32014, 33661, 31401, 32742, 32000, 13, 31208, 13, 36095, 30410, 32327, 32013, 34504, 32004, 33801, 32240, 32551, 44292, 38033, 31614, 32085, 13, 31034, 33172, 29871, 30410, 29871, 30410, 29871, 30410, 34728, 32727, 32746, 41407, 29871, 30410, 29871, 31232, 29871, 30410, 32938, 31643, 29871, 32583, 35401, 33172, 29871, 43566, 29871, 30410, 13, 32009, 35353, 32256, 32461, 13, 32459, 32013, 30410, 13, 30410, 40123, 34504, 30410, 13, 32009, 39108, 39898, 32664, 32907, 32017, 35240, 13, 31643, 42578, 32009, 35688, 32649, 30410, 32009, 13, 32278, 36095, 30410, 40123, 34504, 46225, 32043, 13, 35628, 32992, 55304, 40818, 60732, 31452, 39741, 227, 191, 143, 13, 32278, 31344, 29871, 30410, 32561, 34322, 32286, 32366, 35096, 37024, 29871, 30410, 29871, 32551, 29871, 30410, 33984, 29871, 31034, 13, 33801, 32019, 30410, 13, 32242, 31034, 32208, 32106, 31643, 33563, 39741, 34728, 13, 37609, 32013, 34504, 30410, 49265, 56435, 32354, 13, 32009, 39108, 31326, 32028, 35028, 32060, 33247, 13, 31614, 32039, 35984, 32009, 31034, 49428, 32742, 32000, 13, 32278, 36095, 33120, 32013, 34504, 32664, 33039, 32325, 32551, 39743, 46077, 13, 33631, 32011, 40847, 32325, 32845, 33313, 41841, 32000, 13, 32278, 32885, 32013, 34504, 30410, 32009, 13, 50332, 31452, 32354, 32382, 35054, 32376, 32039, 31034, 32009, 13, 32278, 31344, 48284, 32017, 32201, 33523, 33661, 32742, 32000, 13, 32305, 30410, 32415, 32013, 44922, 30085, 32026, 34027, 32085, 13, 32278, 31208, 31208, 32703, 50390, 35765, 32432, 32137, 32240, 29914, 13, 32445, 34906, 32356, 32379, 32000, 13, 32278, 30474, 49268, 49730, 35312, 31104, 30410, 13, 31208, 32198, 59022, 32003, 44572, 32060, 31208, 32975, 13, 37684, 32016, 32016, 31344, 32327, 32354, 32887, 32745, 32742, 32000, 32248, 13, 44317, 32180, 31401, 13, 34441, 33120, 32013, 34504, 32007, 32561, 38886, 37955, 38033, 31614, 13, 31326, 50414, 32009, 35681, 32004, 30410, 49265, 32611, 13, 31326, 34089, 32009, 31034, 32003, 45911, 30410, 33184, 32013, 30410, 13, 32371, 31034, 32548, 33801, 32010, 32551, 35551, 32009, 39697, 32009, 13, 32383, 32579, 45196, 31601, 32003, 32432, 32461, 13, 33250, 32318, 33216, 32018, 32120, 32664, 40803, 32009, 32878, 32205, 32013, 39909, 31034, 32000, 13, 32316, 29955, 13, 13, 50390, 32325, 38398, 32649, 32017, 35312, 42384, 33317, 32088, 47124, 35964, 31644, 33313, 31326, 31643, 32000, 13, 32271, 29929, 13, 13, 32543, 42379, 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+inputs:
+<s> [INST] Extract the bibliographic TITLE from the Tibetan segment below. Reply with JSON only using the key "spans". Each span must include "text", "start", and "end" (0-based character offsets relative to the segment text, inclusive at end). Every span text must be an exact substring of the input. If there is no title, reply: {"spans": []}.
+ང་
+ཀ་དཀར་སོ་རང་སར་་ན་ ག ་༢ ཏང ཞིང
+མམཏིཾ་དྭང༌བཏིང་སགྷ་མགང༌ནུ ཏིང
+སྣང་ཐལ་ཐོ་ཆད་འབྱུང་ངོ༌།
+རྟོགོས་ན་དྭངས་མའི་ཡན་ལག་ལྔ་སྤྲུལ།
+འོད་ལྗང་གྲུ་ས་འཛིན་
+དོདཪིང་ མམ་མས་རྒྱུ སག་
+མསྒ་ཉངས་གསས་ས་གདས་བཅས་
+་ཤ།
+৬ই
+འདོ་སྦྲང་གྲུ་ས་ཡྟོས་པ་དེའི་བྱུང་གི་ཡན་
+ལག་ཞབས་གསས་པའི་ རྣ་༼སྤུན་
+ཐོཾ་ཤར།
+མ་ཏོགས་ན་འབྱུང་བའི་བཅུད་སོཌ་ཀྱིས་སྣོད་ལྔ་ཆགས།
+བོདདཀར་སོ་ལ་འཛིན་ས་
+འདོང༌ཡོར་འཛིན་ས་གེ་
+སེ་ཡན་མག་མ
+བརོ།
+ཕིང་
+འོདོ་དམར་སོ་གྲོལ་བ་དེའི་སོའི་ཡན་
+མག་ཕྱག་གཡས་སའི་རྣམ་སྦྲུས་
+ཐསས་སྨད་ཤར།
+ལད་སོགས་སོ་ལ་འཛིན་ས་དོན།།
+ཅུཤིང་ མག་བབང་ཉ་སུ་ན བ ནང་
+ས་།
+৬ই
+འད་སོགས་སོ་འཛིཉ་སད་དུ་ཚོཊ་བཞརམའི
+ཨམ་ ས ན་- བས ་གཡོག་སའི་རྣམ་
+སྤྲུན་ཐོད་པུང་ངོ།
+འོད་སེར་སོ་རང་སར་ཨོན་ནས་སཆི་ མག་
+ཀག་ཕྱག་གཡོན་སའྀ་ ཟྭ་སྤྲུན་
+བོད་འབྱུང་ངོ༌།
+
+འདོ་སྔོན་ཡོ་ལ་འཛིན་ས་
+དེ་འབྱུང་བ་ཅུའི་བཅུད་སོཌ་པའི་
+ཆ༽
+འོད་སེར་སོ་ལ་འཛིན་བ་སྐ
+དེ་འཟུང་བ་སའི་བཅུད་སམས་པའི་ངོ་
+གོད་ཕོ་བ་ཆགས་།
+ན༽
+འོད་སེར་སོ་འཛིན་ཡོད་དུ་སྤྲིན་པས་
+ལྟ་ཁོད་ཀུན་ཁྱེད་ཤ་འཛིན་གྱི་
+མཛོང༌ཤར༌།
+དོ་སྦྲང་གུ་རྩ་༣༧།ང་
+དེང་འགྱུང་བ་རྣ་མཝའི་བཅུད་
+དེས་འབྱུང་བ་རླུང་གི་བརྒྱུད་སོང་
+སོ་ར་གས་་བ་མགས།
+སྒ་རུ་ཀོང་བགས།
+འདོ་དཡར་སོང་ས་འཛིན་ཡང
+དེངས་འབྱུང་བ་ཡེའི་བཅུད་སོགས་
+ང་སང་ས་མཉས།
+སྒང་སྒང་ས་མགས་།
+ལོ་དཀར་སོ་འཛིན་ཡོད་དུ་གྲལ་བས་
+འདོ་ལྗང་གུ་འཛིན་ཡོད་དུ་ཡྟོན་བས་
+འདོ་་ཡར་སོ་འཛིན་མེད་དུ་
+གྲུང་འབྱུང་ཡིད་བཞིན་གྱི་མཛོང་/
+ཡང་ཁྱོད་་བྲགས་འཛིན་གྱི་མཛོད་
+་གྱི་མཛོང་ཤར
+༼བར་ང
+བར་།
+འདོ་རྔན་སོ་འཛིན་ཡོད་དུ་སྤྲོས་བས་ཧྲུང་
+རྩོད་ཀུན་གསོ་ཁྲག་འཛི་ཉིད་གྱི་
+མཛོད་ཤར།
+༣གོས་ན་ཀུན་འབྱུང་གི་མཛོད་ལྔངུཤར།
+
+མ་དྭགས་ན་ཟག་བཅས་ཀྱི་་བ
+ཧོ་དཀར་སོ་མ་འཛིར་ས་ང་
+གྱེས་ས་དམ་གམ་སདི་སྒོ་མོ་
+འག་གི་དབང་བོའི་སྒོ་ད།
+ཀ་དཀར་སོ་བཛིན་ཡོད་དུ་མན་བས་
+རྩྭ དང ་ འཕེ ད ན གཤས ཇ ང མ གྱི ས ར ཟ ད ས པའི ཐཱ
+སྒོ་བར་
+རྟགས་ན་ཟག་མེད་གྱི་བང་ས་ལ་ཤར།
+དོ་ལྗང་ཟླ་ལ་འཛིན་ས་
+སྐྱེབསས་བྱུང་གི་སྒོ་མོ་སྣ་
+ཏྭཾ ཁ ད འ སོ མཞེ༼ཤར།
+གོ་ལྗང་གུ་རང་སར་ཥིན་པས་
+ཤངའགྱི་དབང་སོའི་སྒོ་ཤར།
+ཀོད་་ཡར་སོ་ས་འཛིང་
+ཉེན་སྐྱེ་སས་མིའི་སྒོ་སོ་
+ལྦེའི་དཔང་སོ་མ་ཀར།
+கூ
+བོདོ་་མ���་སོ་འཛིན་མེད་དུ་ཁོས་
+པས་ལྤགས་གྱི་་ཟང་སོའི་སྒོང་༼ཤར་ང/
+འདོ་སོག་སོ་ས་འཛིན་ས་ང་
+དེས་ཆུའི་སྒོ་མོ་རྣ་བའི་དབང་
+སོངས་་་།
+༧
+འདོ་སྔོན་སོ་འཛིན་མེད་དུ་སྟོལ་བས་
+རྒཥཱ་གྱི་སྒོ་མོ་ཤར༌།
+འདོ་སེད་སོ་མ་འཛིན་
+ས་དོས་སའི་སྒོ་སོ་ལུས་་བང་
+སོ་ས་ཤར་
+འདོ་སེར་སེ་རང་སར་ཡྟོན་བས་སྒྱཏི་
+དབང་སོའི་ཁོང་ཤར།
+
+གཟུང་འཁྱོད་མིག་གི་རྣམ་ཤེས
+ཀར་།
+ཀོད་་ཀར་སོངས་འཛིན་ས་
+དེས་གས་མའི་ལན་མས་
+རྨ་ལྗང་གྱ་ལ་འཛིན་ས་
+་བྱུང་གིསམས་ནས་དྲི
+ཁཱའི་སྒོམ་༼ཤོས་ཀར།
+ཆས་མས་དྲི་འགྱོད་
+ཧོདོ་དམར་སོ་མ་ན་
+ས་ངོས་མའི་ཨས་སས་སྨན་
+ཞས་༼ཤེས་༼ཤར་།
+ཧོ་དཀར་སོ་གྲྭ་
+འོདོ་ལྗང་གླ་ཥིན་པས་ཕེ ་གསམ་
+བེད་་ཡར་སོ་ལྟ་་པས་བནི་ཉྱིད་རོ་
+༩ངབགྱི་
+ཤེས་ས
+གསལ་སྦྲགས་ཀྱི་༼ཤང་ས་ཤར།
+ག་ན་ས་
+འདོ་། ་ས་ལ་་ིས།
+ས་དེས་ཆུའི་ཡས་ལས་ཞ་
+བའི་རྣས་༼ཞེས་ཤར༌།
+ཇི་
+འོམ་པོན་སོ་ཁྲོལ་བས་མངལསའི་ སྣ་
+གསལ་ལྷན་གྱི་༼ཤེས་བ་ཤར།
+གོ་སེར་སོ་ལ་འཛིན་
+ས་དེ་མགོོ་ཧས་མས་ལུས་
+གི་རྣས་༼ཤེང་ཀར་་
+སོ་ན་བ པས་རེག་
+སྨྱའི་ཤེས་ས་ཤར།
+ཡ་ཤོང་ན་༼སྤྱོད་སའི་སྤྲུལ་ལྔ་འར།
+གོ་་འརས་ལ་
+འཛིན་སས་ན་མཁའི་ཡས་
+མས་མིག་ག་ ཡུན་དུ་གཟུ་
+རྩི་བྱེ་ལྗག་ཡོངས་༼བོད་དུ་ཤར།
+འོདོ་་ཀར་སོ་འཛིག །ཡོད་དུ་སྟོན་བས་
+དེའི་གཟུགས་རྣམ་སར་དག་པ་༼སྤྱང་༼
+༧ཁྱས་དུ་ཤར།
+འདོ་ལྗང་གུ་ས་འཛིན་
+ཞེས་བྱུང་གི་ཡས་མས་
+ཁཱའྀ་ཀུམ་དུ་ཊིའི་བྱེ་ཟག་མོངས
+རོ་ཐོ་▪
+རྨ་ཤར།
+འདོ་ལྗང་གུ་འཛིན་ཡོད་དུ་ཨོན་པས་
+རྣམ་སར་་ག་ས་༼འ་འགྱི་
+ཁུལ་དུ་ཤར།
+འདོ་་མར་སོ་སྤྲིས་པས་རོ་ རྒས་སར་
+དག་པ་སྦྲགས་ཀྱི་ཀུན་དུ་ཤར་།
+འདོསམར་སོ་མ་འཛིན་
+བལེའི་ཡལ་ལས་ལྦའི་ སྤུན་
+བོདོ་སྔོན་སོ་ལ་འཛིག
+སས་ཆུའི་རྩན་མས་རྣ་བའི་
+ཤེས་སའི་ཡུལ་དུ་སྒྲིའི་སྨྲེ་གྲག་སོངས་
+༼་་ཤར།
+ཉེ༽
+འདོ་སན་སོ་སྤྲིན་པས་ཁྭ་ བྷས་སར་
+ངག་ས་ལྡན་མི་ཕམ་དུ་སྤར་ང
+ཧོ༑་སིར་སོ་མ་
+ཡེ་པ་བའི་ཡས་མས་
+ལུས་གྱི་བཱས་སར་ཤེས་སའི་ཨུ སང
+བྱ་རེག་ཀྱིས་ཐེ་ལྗག་ལོང་༼སྟད་དུ་ཤར།༽
+འོདོ་སེར་སོ་སྤྲོས་བས་རེག་བྱ ། རྣམ་
+སར་དག་ས་རྒུའི་ཕུལ་དུ་ཤར༌།
+འདི་བ་
+སྒོ་ངག་གི་སྤྱས་ལྔ་ཤར་ང
+166
+
+སེམས་སྡེ།
+འཕོ་བ་གསལ་འདེབས།
+
+ས་ཉོད་ན་རྒྱུ་དུག་ལྔ་རྒྱུ་སར།
+འདོ་་ཀར་མ་ཛིན་
+འདེ་ཞི་མམའི་སྩལ་མས་
+ཥོ་ཁོང་ས་ཞེ་ནང་ཤར།
+ཀོདོ་དགར་སོ་རང་སར་སྤྲོལ་བའི་སྐྱེ་
+ས་སོན་སོའི་སྐོ་ས་ཀར།
+འདོ་ལྗང་གྲུ་ན་སླུམ���
+ས་ན་བྱུང་གི་ཡས་མས་ཉོའི་
+ཁོངབས་ང་རྒྱས་སྤར།
+རང་སརང༔
+འདོ་ལྟ་་གུ་གིས་བཏིང་ ཆལ་མས་
+ཞི་བ་མེན་སོ་ཉོབས་༼ཀར༌།
+གོ་་སྐྱུར་སོ་ལ་འཛི་
+ངེས་ཤི་་ལ་མས་ཉོན
+ཁོངས་ས་འདོདམགས༼ཤར༌།
+དོ་་ཡར་སོ་རང་སར་གྲོས་བ་དེ་
+༦ ༢ ༩༢ ༢༥ ཙྪན, ༤་།, ཨཱ?
+སྟོབས་༼ཤར༌།
+གཏོ་སྔོན་སོ་ལ་འཛན་
+སདེས་པུའི་ཨན་ལས་ཉཥོ་
+མོངསས་ཕྲག་ཏོག་ཤར༌།
+འདོ་པའི་སོ་རང་སར་སྙོལ་ངའདེའི་
+ས ས ་ བཞི ས ང མ ང ས ས ་ ཚོ་ཁོངས་
+སྐབས་ཤར།
+གོདོ་སེར་སོ་ལ་འཛི་
+སར་ཞུགགས་དང་ཆས་མས་
+རྒན་ཡོང་བས་གཏི་ ཡུག་ཏུ་ཤར།
+འདོ་སོར་སོ་ཛྭ
+་་ V
+མལ་ལས་ཡེང་མེད་ཡོངས་
+སྐབས་༼
+ཤར།
+རྐོང་རྒྱུུ་ལྷན་ སྒྲུབ་ལྡོས ་ལ་ཤར
+ཡ་ཤོ་ཞུ་དྲུག་ལའི་སས་ཡོད་པལྔ་འབྱུང༌།
+དོ་དཀར་སོ་ལ་འཚའོང་
+ཉེ་ཞེ་སང་དི་ མས་སུཏ
+གོ་ལྗང་གུ་ནྡྲ་“མའི
+ག་དེ་ཚ་ཚས་མས་མིག་
+ཆུ བ ་ ངག་ཉང
+ས ་ གྲྭ་པས་ཞེན པ
+ཁོ་ཤར།
+རྙོག་གཅོད་ཡངག་སེས་གདུག་
+ཟས་ཤར།
+བོད་དཀར་ས་རང་སར་སྔོན་
+སྩས་ཀས་ཀྱི་ས་མོན་སོཔོ་ཟླམསང/
+གོང་ས་རྒོད་སོང་བར།
+བ་ནང་ཧན་གྱི་ཀློ་
+འ་གླང་གླ་རང་སར་བ་་བ་དེའི་ཐོར་མ་
+སས་ཞི་བ་མོ་སའི་སྐོམ་གྱིས་ཀྱ་
+ཀ་་ཡར་ས་ས་
+འཛིན་པ་དེན་འདོ་མ་ལས་
+སེར་སྒ་འཚུར་འགེཥ་འཛིན་མང་
+སྱ་ཤར།
+འགོ་དམར་སོ་སྒྲོལ་བ་དེ་་་་་སས་
+ལྕན་ས་ལེག་སོའི་སྐབས་ནུ་སོར་
+སྙོགས་པའི་ཡེས་ ཀར༌།
+འདོ་སྔོན་སོ་ས་
+གཛིན་ས་དེས་འགྲག ་་འོག ང་ པར་ ཡང ང
+མེ་ཆུང་རུ་་འསྨད་གསོད་གྱི་མས་
+w
+༼ ཀར།
+ཐ༽
+འམ་པཱཥོ་སོ་ཉང་བར་སྤྲོལ་ བ་དེད མཆ དའ་
+མས་ ་ས་ ་ ས ་ ོག ་ཞིའི་ ཉབས་སྲུང
+་ཉལ་བ་རྩ་གྱི་ཡོས་
+ཀ༢།
+སྨོད་ནོར་སྒོ་ས་འཛིན་
+འདེས་ གཆི་ཡུག་གི་མས་སྲུ་
+བཾ་རྨོངསལྐོག་གསོང་སྐུ་ཁྲོཥ་
+ཥོ་སོག་གི་མས་སྤར།
+འདོ་སེར་སོ་མོར་བའ་ཡེས་ཆེན་སོངཧོ་
+རྐོས་གྱིས་ན་ཡང་རྗེས་
+རྐོ་ན་བསྒྲིབ་སོད་གྱི་ལེ་
+
+ས་རྙོངསག་སྨོན་པའི་
+ཁུང་སོ་ལྔ་ཤར་ ། ། འཁྲུལ་སའི་ཁྱ་་ལྔ་ནུ་
+འདོ་་ཀར་སོ་ལ་འཛིའི
+ས་དོས་འཁྲས་བུ་རྣམ་སར་ཥ་
+སའི་ཕུང་པོ་འང༌། ས་རིག་འབྲུསང
+པའི་བད་རྒུད་
+ཀོད་དཀར་སོ་མདོན་དུ་སྲོལ་བས་་སྲུས་
+ཕྱོགས་ གཤེག་ལྷའི་ ༢:ཤར་ ཀུན་
+ལྗང་སྦས་པའི་ རྒུར་གསས་
+ཐོ་ན་གྲུབ་སའི་ལྷ་ལྔགས་ཤར༌། ། རྒྱས་བ་
+མ་རྐོ་ག་སྨྱོ་བའི་སྒོ་ལར་འཇུག
+དོ་ཀླཌ་གྲུ་ལ་འཛི།
+དདེས་་གྲས་གྲུ་འ་་བྱེད་གྱི་པུང༌
+སོ་ཤར་། སྒྱུ་ས་གཟུཌ་བརྙན་གྱི་
+དུ་སྡུཁ།
+ོད་
+རྫངགུ་མདོའུདུ་གྲོལ་བས་སྦྱང་
+ཁོགས་གར་གསས་གྱི་{་ཤར་ ་ནི་ལྷ་
+གར་ཕྱུག་ག���་ཀུར་གསམ་
+རྨོད་་མར་སོ་ས་བཛང་
+ས་དེས་འཅས་གུ་གདུ་༼ ཤེས་གྱི་ཕུང་\
+སངཤར་ ། ཅགས་འཁོར་རྒན ཏ ཨིན ཏེ, ཐཱཝ ཏྭཱ
+ཀྱི་བྱ་ད་ཞུས།
+འོདོ་་སར་སོ་ས་འི་དུ་གྲོལ་བས་ནུབ་ཕྱོགས་
+གསྣང་གསལ་གྱི་རྟ་ཤར་ ཀྱེ་ཛག་
+དངོས་ཡོད་ཀྱི་རྒྱུར་གསམ།
+མེད་སྔོད་པ་ས་འཛིན་
+པ་དེས་རྫས་བྲུ་བར་བའི་ཕུང་
+འ མི་ བདག་བཏན་ བཙན་
+བཤརུང་རྒུང༌།
+་ག་་པ་
+ཉེ་སྔོའི་ས་ལ་ཡངའི་དྲུདུ་གྲྭན་པས་ལྷ་གྱི་
+་ནོད་གནས་ཀྱི་རིཌ་ཀར་
+སྙུ་གྲུབ་ཀྱི་སྐུར་གསས།
+འདོ་སེར་པོ་ལ་འཛག་པ་
+དེ་ གཁྲ་་གྲུ ་ ག རྒྱུ ། ་ གྱི་ཕྱུ དང ་
+སོ་ཁྲུས་མེེན་ཁྱི་ཁྲུད་ཞུ༌།
+འདོ་སར་སང་ཡང་ཡདོ།་འར་ ་ བ་ ་ ཤར ་
+ཕྱོགས་གསས་རྗེ གི་རི ་ ཤར་གསམ་བ་
+རང་འགྱུང་གི་ སྒུར་པ
+མདོ་ཀར་པོ་ལ་འ༤་ས
+ཤོན་མཐོའི་ཚལ་ལན་
+མྱེངས་རྣམ་བཞིའི་སྒོ་ཤར༌།
+འདི་་ལྟར་སི་ན་མང།
+གྲུས་སྒོགས་དེ་བཞི།་
+་བས་
+རྐོ་ན་གྲུབ་ཀི་་རིག་ལྔར་སྤྲོན་
+མ་རྟོང་འ་འདུ་བའི་ཞད་ལྔ་ལྟུང༌།
+རྒོད་དཀར་སོ་ལ་འཛིང
+વીર્યવતી ભોમ
+འ་འདུ་བ་རྣས་ས་བམིའི་གགིང་གང་
+དོ་ལང་གྲུ་ལ་འ་
+འདེ་བླད་གི་མས་རྫས
+མྱོས་པའི་སྒོ་ཤར་་
+ཞི༽
+གོ་ལཌ་གུ་ཡང་དུ་
+ལས་ཀྱི་ཎྜ་ཤར།
+་་་༥་ཙྪ་་
+ཀ་ལྗང་གུ་ལ་
+འཛིན་པ་དེས་༔ ད་་གང་ད་
+ལས་གད་འདུ་གི་གཞིང་ཤར།
+ག
+དོ་་ཀར་སོ་ལ་ཡའུདུ་སྤྲིན་པས་
+ས ད ་ ་ ་ ང ཨཱཎ ་ ར ་ ཁམ ་ཏཿ ད ནཱ ་
+ས་ཀྱི་རང་བཞིན་
+ཀར་་
+་་མར་སོ་
+ས་དེས་ཡེ་འྀ་མལ་བ
+མྱེས་གི་སྒོ་ས་
+འདོ་་མར་སོ་ལ་ནི་དུ་
+ནུབ་དྨ་ཎྜི་ཤར་༌
+འད ་༥ཞི་བོ་ཡ་མ་ཉི ་ དུ ་ ག ས
+ཡ་དེ་་
+པས་ལྷ་རེམ་རིག་ཤར་ ང
+སེར་སོ་ས་འཛིན་
+ས་དེས་བའི་མན་ལས་མས
+ནལ་སྐྱེས་སའི་སྒོ་ཤར།
+འདོ་སེར་སོ་འ་མདོང་དུ་སྒྲོས་པས་
+ཤར་པ་ཁྲུང་རིགས་སར།
+འདོ་དམར་སོ་ས་
+འཛིན་དེས་གཞི་ཆལ་སས་
+འད་འདུ་བ་མཁས་པའི་གཞི་ཤར།
+༢་ མར་སོ་མï་དུ་གྲོལ་པས་
+འགག་མེད་གསུང་གི་རང་བཞིའུ/
+༼ ཀ༨༤།
+འ‹་སོང་བས་ལ་འཛོ་
+ག་དེས་ཅུའི་ཡལ་ལས་གད་
+འདུ་བ་བད་ཀན་ཕྱི་གཞི་ཤར།༽
+བཞིན་བར་ང
+མདོ་སེར་སོ་ལ༥ཥསྤྲིན
+བཤེས་བའི་་ལ་་ས་འདུ་
+བ་འདུས་སའི་ གཞི་ ཤར་་
+པར་སངས་ཡ་ནི་དུ་སྔོས་ཙས་
+ཡོད་རྒུའི་རང་བཞིན་
+ཐོག་ག་ཟླ་ཡོད་ཀྱི་འབྲས་བུ་ལྔར་སྤྲོས།
+167
+
+གསུང་རབ་སྒོ་མཛོད་རིན་པོ་ཆེའི་གླེགས་བམ།
+139
+
+་བསྡོད་པའི་ ལམ་ལྔ་བརྒྱུད༌།
+ཤོ་་་འར་སོ་ན་འམང་
+ས་དེས་་མཐའི་
+་བའི་ལ
+རོ་ལྗང་གླ་ལ་འཛ
+པ་དེས་ཀླུང་གི་ཡས་ལས་
+ལྷསང་ལྷ་མིན་དུ་འགྲོ་བའི་ལང༼ཤར་
+དོ་་ཀར་སི་ཡངནི་དུ་པར་པས་��ྣུན
+བྱས་ནི་མཁའི་དཀྱིས་
+བར་ང
+ཕ་
+གོ་ལྗང་གླར་ལྟོས་བས་སྤང་ཕྱི་
+འདེགས་ཉིད་བྱུང་གི་་ཕྱིས་འཁོར་
+འདོ་དམར་ས་མ་
+འཛིན་པ་དེས་གེ་འི་སང་༧་༥༥་
+མི་ཅི་མས་དུ་འགྫོ་བའི་ ནམ་ཤར་ང༽
+ཕ་
+འདོ་་མར་སོརསྔོན་པས་ནུབ་གསལ་
+ཆོད་སེའི་ དཔྱིས་འཁོར་ཤར།
+རོ་པའི་ཡ་༥་
+འཛིན་ས་དེ་ཐུའི་མན་
+མས་ཡིད དྭཌདསུ་འགྲོ་བའི་ མ [/INST] {"spans": []}</s>
+label_ids:
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+labels:
+{"spans": []}</s>
+
Running tokenizer on dataset (num_proc=8):   0%|          | 0/100 [00:00<?, ? examples/s]
Running tokenizer on dataset (num_proc=8):  13%|█▎        | 13/100 [00:00<00:02, 30.70 examples/s]
Running tokenizer on dataset (num_proc=8):  26%|██▌       | 26/100 [00:00<00:01, 52.75 examples/s]
Running tokenizer on dataset (num_proc=8):  64%|██████▍   | 64/100 [00:00<00:00, 131.30 examples/s]
Running tokenizer on dataset (num_proc=8):  88%|████████▊ | 88/100 [00:00<00:00, 152.53 examples/s]
Running tokenizer on dataset (num_proc=8): 100%|██████████| 100/100 [00:00<00:00, 106.85 examples/s]
+eval example:
+input_ids:
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33313, 36091, 32548, 43404, 44292, 52791, 33327, 32000, 29871, 32000, 32415, 32197, 34579, 31896, 33097, 32354, 32278, 31344, 33189, 32237, 32000, 29871, 32000, 29871, 43887, 31104, 32325, 37024, 31344, 32016, 32551, 32354, 59022, 32012, 32802, 41989, 32013, 33261, 32255, 32248, 13, 38006, 34016, 32000, 29871, 31034, 45836, 48016, 32992, 34050, 32354, 42995, 35501, 32489, 31601, 31326, 32120, 34579, 35312, 31344, 32203, 35482, 31104, 33313, 34504, 32000, 29871, 32000, 29871, 32000, 29871, 32000, 50585, 52585, 32016, 37875, 32418, 32030, 32002, 29871, 31034, 41442, 32354, 48963, 518, 29914, 25580, 29962, 8853, 1028, 550, 1115, 5159, 29913, 2]
+inputs:
+<s> [INST] Extract the bibliographic TITLE from the Tibetan segment below. Reply with JSON only using the key "spans". Each span must include "text", "start", and "end" (0-based character offsets relative to the segment text, inclusive at end). Every span text must be an exact substring of the input. If there is no title, reply: {"spans": []}.
+ དངོས་པོ་ཀུན་གྱི་རང་བཞིན་ ༼༢༽
+སྟོང་། ། གང་ཕྱིར་དངོས་རྣམས་ཐམས་ཅད་ཀྱི། ། རང་བཞིན་རྒྱུ་རྐྱེན་ཚོགས་པ་འམ། ། སོ་སོ་དངོས་པོ་ཐམས་ཅད་ལ། ། ཡོད་མིན་དེ་ཕྱིར་སྟོང་པ་ཡིན། ། ཡོད་ཕྱིར་ཡོད་པ་སྐྱེ་མིན་ཏེ། ། མེད་ཕྱིར་མེད་པ་སྐྱེ་མ་ཡིན། ། ཆོས་མི་མཐུན་ཕྱིར་ཡོད་མེད་མིན། ། སྐྱེ་བ་མེད་པས་གནས་འགག་མེད། ། གང་ཞིག་སྐྱེས་དེ་བསྐྱེད་བྱ་མིན། ། མ་སྐྱེས་པ་ཡང་བསྐྱེད་བྱ་མིན། ། སྐྱེས་པ་དང་ནི་མ་སྐྱེས་པའི། ། སྐྱེ་བཞིན་པ་ཡང་བསྐྱེད་བྱ་མིན། ། འབྲས་བུ་ཡོད་པས་འབྲས་ལྡན་རྒྱུ། ། རྒྱུ་མིན་དང་མཚུངས་མེད་པ་ཡང་། ། མེད་དེ་ལ་ཡང་རྒྱུ་མིན་མཚུངས། ། ཡོད་མིན་མེད་པའང་མིན་ན་འགལ། ། དུས་གསུམ་���ྣམས་སུ་འཐད་མ་ཡིན། ། གཅིག་མེད་པར་ནི་མང་པོ་དང་། ། མང་པོ་མེད་པར་གཅིག་མི་འཇུག། དེ་ཕྱིར་རྟེན་ཅིང་འབྲེལ་འབྱུང་བའི། ། དངོས་པོ་མཚན་མ་མེད་པ་ཡིན། ། རྟེན་འབྱུང་ཡན་ལག་བཅུ་གཉིས་གང་། ། སྡུག་བསྔལ་འབྲས་ཅན་དེ་མ་སྐྱེས། ། སེམས་གཅིག་ལ་ཡང་མི་འཐད་ཅིང་། ། དུ་མ་ལ་ཡང་འཐད་མ་ཡིན། ། རྟག་མིན་མི་རྟག་མིན་བདག་དང་། ། བདག་མིན་གཙང་མིན་མི་གཙང་མིན། ། བདེ་མིན་སྡུག་བསྔལ་མ་ཡིན་ཏེ། ། དེ་ཕྱིར་ཕྱིན་ཅི་ལོག་རྣམས་མེད། ། དེ་མེད་ཕྱིན་ཅི་ལོག་བཞི་ལས། ། སྐྱེས་པའི་མ་རིག་མིན་སྲིད་ལས། ། དེ་མེད་འདུ་བྱེད་མི་འབྱུང་ཞིང་། ། ལྷག་མ་རྣམས་ཀྱང་དེ་བཞིན་ནོ། ། མ་རིག་འདུ་བྱེད་མེད་མི་འབྱུང་། ། དེ་མེད་འདུ་བྱེད་མི་འབྱུང་ཞིང་། ། ཕན་ཚུན་རྒྱུ་ཕྱིར་དེ་གཉིས་ནི། ། རང་བཞིན་གྱིས་ནི་མ་གྲུབ་ཡིན། ། གང་ཞིག་བདག་ཉིད་རང་བཞིན་གྱིས། ། མ་གྲུབ་དེ་གཞན་ཇི་ལྟར་བསྐྱེད། ། དེ་ཕྱིར་གཞན་ལས་གྲུབ་པ་ཡིས། ། རྐྱེན་གཞན་དག་ནི་སྐྱེད་བྱེད་མིན། ། ཕ་ནི་བུ་མིན་བུ་ཕ་མིན། ། དེ་གཉིས་ཕན་ཚུན་མེད་མིན་ལ། ། དེ་གཉིས་ཅིག་ཆར་ཡང་མིན་ལྟར། ། ཡན་ལག་བཅུ་གཉིས་དེ་བཞིན་ནོ། ། ཇི་ལྟར་རྨི་ལམ་ཡུལ་བརྟེན་པའི། ། བདེ་སྡུག་དང་དེའི་ཡུལ་མེད་པ། ། དེ་བཞིན་གང་ཞིག་ལ་བརྟེན་ན། ། གང་ཞིག་རྟེན་འབྱུང་དང་འདིའང་མེད། ། གལ་ཏེ་དངོས་རྣམས་རང་བཞིན་གྱིས། ། མེད་ན་དམན་མཉམ་ཁྱད་འཕགས་དང་། ། སྣ་ཚོགས་ཉིད་ནི་མི་འགྲུབ་ཅིང་། ། རྒྱུ་ལས་ཀྱང་ནི་མངོན་འགྲུབ་མིན། ། རང་བཞིན་གྲུབ་ན་རྟེན་འབྱུང་གི། ༼༣༽
+དངོས་པོ་མེད་འགྱུར་མ་བརྟེན་ན། ། རང་བཞིན་མེད་པ་ག་ལ་འགྱུར། ། དངོས་པོ་ཡོད་དང་དངོས་མེད་ཀྱང་། ། མེད་ལ་རང་དངོས་གཞན་དངོས་སམ། ། དངོས་མེད་འགྱུར་བ་ག་ལ་ཞིག། དེ་ན་རང་དངོས་གཞན་དངོས་དང་། ། དངོས་མེད་ཕྱིན་ཅི་ལོག་པ་ཡིན། ། གལ་ཏེ་དངོས་པོ་སྟོང་ཡིན་ན། ། འགག་པ་མེད་ཅིང་སྐྱེ་མི་འགྱུར། ། ངོ་བོ་ཉིད་ཀྱིས་སྟོང་པ་ལ། ། གང་ལ་འགག་ཅིང་གང་ལ་སྐྱེ། ། དངོས་དང་དངོས་མེད་ཅིག་ཅར་མེད། ། དངོས་མེད་མེད་ན་དངོས་པོ་མེད། ། རྟག་ཏུ་དངོས་པོའང་དངོས་མེད་འགྱུར། ། དངོས་མེད་མེད་པར་དངོས་མི་སྲིད། ། དངོས་པོ་མེད་པར་དངོས་མེད་མིན། ། རང་ལས་མིན་ཞིང་གཞན་ལས་མིན། ། དེ་ལྟ་བས་ན་དེ་མེད་ན། ། དངོས་པོ་མེད་ཅིང་དངོས་མེད་ན། ། ཡོད་པ་ཉིད་ན་རྟག་ཉིད་དང་། ། མེད་ན་ངེས་པར་ཆད་ཉིད་ཡིན། ། དངོས་པོ་ཡོད་ན་དེ་གཉིས་འགྱུར། ། དེ་ཕྱིར་དངོས་པོ་ཁས་བླངས་མིན། ། རྒྱུན་གྱིས་ཕྱིར་ན་འདི་མེད་དེ། ། རྒྱུ་བྱིན་ནས་ནི་དངོས་པོ་འགག། སྔར་བཞིན་འདི་ཡང་མ་གྲུབ་ཅིང་། ། རྒྱུན་ཆད་པར་ཡང་ཐལ་བར་འགྱུར། ། སྐྱེ་འཇིག་བསྟན་ཕྱིར་སངས་རྒྱས་ཀྱི། ། ལམ་བསྟན་མ་ཡིན་སྟོང་ཉིད་ཕྱིར། ། འདི་དག་ཕན་ཚུན་བཟློག་པ་རུ། ། མཐོང་བ་ཕྱིན་ཅི་ལོག་ལས་ཡིན། ། གལ་ཏེ་སྐྱེ་འགག་མེད་ཡིན་ན། ། ཅི་ཞིག་འགགས་པས་མྱ་ངན་འདས། ། རང་བཞིན་གྱིས་ནི་སྐྱེ་མེད་ཅིང་། ། འགག་མེད་གང་དེ་ཐར་མིན་ནམ། ། གལ་ཏེ་འགག་ལས་མྱ་ངན་ཆད། ། གལ་ཏེ་ཅིག་ཤོས་ལྟར་ན་རྟག། དེ་ཕྱིར་དངོས་དང་དངོས་མེད་དག། མྱ་ངན་འདས་པར་རུང་མ་ཡིན། ། གལ་ཏེ་འགོག་པར་འགའ་གནས་ན། ། དངོས་པོ་ལས་གཞན་དེ་ཡོད་འགྱུར། ། དངོས་པོ་མེད་ཕྱིར་འདི་མེད་ལ། ། དངོས་པོ་མེད་ཕྱིར་དེ་ལས་མེད། ། མཚན་གཞི་ལས་གཞན་མཚན་ཉིད་ལས། ། མཚན་གཞི་གྲུབ་པས་རང་མ་གྲུབ། ། ཕན་ཚུན་ལས་ཀྱང་མ་གྲུབ་སྟེ། ། མ་གྲུབ་མ་གྲུབ་སྒྲུབ་བྱེད་མིན། ། འདིས་ནི་རྒྱུ་དང་འབྲས་བུ་དང་། ། ཚོར་དང་ཚོར་བ་པོ་སོགས་དང་། ། ལྟ་པོ་བལྟ་བྱ་སོགས་ཅིའང་རུང་། ། དེ་ཀུན་མ་ལུས་བཤད་པ་ཡིན། ། གནས་མེད་ཕན་ཚུན་ལས་གྲུབ་དང་། ། འཆོལ་ཕྱིར་རང་ཉིད་མ་གྲུབ་ཕྱིར། ། དངོས་པོ་མེད་ཕྱིར་དུས་གསུམ་ནི། ། ཡོད་པ་མ་ཡིན་རྟོག་པ་ཙམ། ། གང་ ༼༤༽
+ཕྱིར་སྐྱེ་དང་གནས་དང་འཇིག། འདུས་བྱས་མཚན་ཉིད་འདི་གསུམ་མེད། ། དེ་ཕྱིར་འདུས་བྱས་ཉིད་མ་ཡིན། ། འདུས་མ་བྱས་ལའང་ཅུང་ཟད་མེད། ། མ་ཞིག་མི་འཇིག་ཞིག་པའང་མིན། ། གནས་པ་གནས་པ་མ་ཡིན་ཏེ། མི་གནས་པ་ཡང་གནས་མ་ཡིན། ། སྐྱེས་པ་མི་སྐྱེ་མ་སྐྱེས་མིན། ། འདུས་བྱས་དང་ནི་འདུས་མ་བྱས། ། དུ་མ་མ་ཡིན་གཅིག་མ་ཡིན། ། ཡོད་མིན་མེད་མིན་ཡོད་མེད་མིན། ། མཚམས་འདིར་སྣ་ཚོགས་ཐམས་ཅད་འདུས། ། བཅོམ་ལྡན་བླ་མས་ལས་གནས་དང་། ། ལས་བདག་ལས་ཀྱི་འབྲས་བུ་དང་། ། སེམས་ཅན་རང་གི་ལས་དང་ནི། ། ལས་རྣམས་ཆུད་མི་ཟ་བར་གསུངས། ། ལས་རྣམས་རང་བཞིན་མེད་གསུངས་ཏེ། ། མ་སྐྱེས་གང་དེ་ཆུད་མི་ཟ། ། དེ་ལས་ཀྱང་ནི་བདག་འཛིན་སྐྱེ། ། དེ་བསྐྱེད་འཛིན་དེའང་རྣམ་རྟོག་ལས། ། གལ་ཏེ་ལས་ལ་རང་བཞིན་ཡོད། ། དེ་སྐྱེས་ལུས་ནི་རྟག་པར་འགྱུར། ། ལས་ཀྱང་སྡུག་བསྔལ་རྣམ་སྨིན་ཅན། ། མི་འགྱུར་དེ་ཕྱིར་བདག་ཏུ་འགྱུར། ། ལས་ནི་རྐྱེན་སྐྱེས་ཡོད་མིན་ཞིང་། ། རྐྱེན་མིན་ལས་སྐྱེས་ཅུང་ཟད་མེད། ། འདུ་བྱེད་རྣམས་ནི་སྒྱུ་མ་དང་། ། དྲི་ཟ��ི་གྲོང་ཁྱེར་སྨིག་རྒྱུ་མཚུངས། ། ལས་ནི་ཉོན་མོངས་རྒྱུ་མཚན་ཅན། ། ཉོན་མོངས་འདུ་བྱེད་ལས་བདག་ཉིད། ། ལུས་ནི་ལས་ཀྱི་རྒྱུ་མཚན་ཅན། ། གསུམ་ཀའང་ངོ་བོ་ཉིད་ཀྱིས་སྟོང་། ། ལས་མེད་ན་ནི་བྱེད་པོ་མེད། ། དེ་གཉིས་མེད་པས་འབྲས་བུ་མེད། ། དེ་མེད་ཉེ་བར་སྤྱོད་པ་མེད། ། དེ་བས་དངོས་པོ་དབེན་པ་ཡིན། ། ལས་ནི་སྟོང་པར་ཡང་དག་པའི། ། ཤེས་ན་དེ་ཉིད་མཐོང་བའི་ཕྱིར། ། ལས་ནི་འབྱུང་སྟེ་དེ་མེད་ན། ། ལས་ལས་འབྱུང་གང་མི་འབྱུང་ངོ་། ། ཇི་ལྟར་བཅོམ་ལྡན་དེ་བཞིན་གཤེགས། ། རྫུ་འཕྲུལ་གྱིས་ནི་སྤྲུལ་པ་སྤྲུལ། ། སྤྲུལ་པ་དེ་ཡིས་སླར་ཡང་ནི། ། སྤྲུལ་པ་གཞན་ཞིག་སྤྲུལ་གྱུར་པ། ། དེ་ལ་དེ་བཞིན་གཤེགས་སྤྲུལ་སྟོང་། ། སྤྲུལ་པས་སྤྲུལ་པ་སྨོས་ཅི་དགོས། ། གཉིས་པོ་མིང་ཙམ་ཡོད་པ་ཡང་། ། གང་ཅིའང་རུང་སྟེ་རྟོག་པ་ཙམ། ། དེ་བཞིན་བྱེད་པོ་སྤྲུལ་དང་མཚུངས། ། ལས་ནི་སྤྲུལ་པས་སྤྲུལ་དང་མཚུངས། ། རང་བཞིན་གྱིས་སྟོང་གང་ཅུང་ཟད། ། ཡོད་པ་དེ་དག་རྟོག་པ་ཙམ། ། གལ་ཏེ་ལས་ཀྱི་རང་བཞིན་ཡོད། ། མྱང་ ༼༥༽
+འདས་བྱེད་པོ་ལས་ཀྱང་མེད། ། གལ་ཏེ་མེད་ན་ལས་བསྐྱེད་པ། ། འབྲས་བུ་སྡུག་དང་མི་སྡུག་མེད། ། ཡོད་ཅེས་པ་ཡོད་མེད་ཅེས་ཡོད། ། ཡོད་དང་མེད་ཅེས་དེ་ཡང་ཡོད། ། སངས་རྒྱས་རྣམས་ཀྱི་དགོངས་པ་ཡིས། ། གསུངས་པ་རྟོགས་པར་སླ་མ་ཡིན། ། གལ་ཏེ་གཟུགས་ནི་རང་འབྱུང་བཞིན། ། གཟུགས་དེ་འབྱུང་ལས་འབྱུང་མ་ཡིན། ། རང་ལས་བྱུང་མིན་མ་ཡིན་ནམ། ། གཞན་ལས་ཀྱང་མིན་དེ་མེད་ཕྱིར། ། གཅིག་ལ་བཞི་ཉིད་ཡོད་མིན་ཅིང་། ། བཞི་ལའང་གཅིག་ཉིད་ཡོད་མིན་པས། ། གཟུགས་ནི་འབྱུང་བ་ཆེན་པོ་བཞི། ། རྒྱུར་བྱས་ནས་གྲུབ་ཇི་ལྟར་ཡོད། ། ཤིན་ཏུ་མི་འཛིན་ཕྱིར་དེ་མེད། ། རྟགས་ལས་ཤེ་ན་རྟགས་དེའང་མེད། ། རྒྱུ་དང་རྐྱེན་ལས་སྐྱེས་པའི་ཕྱིར། ། རྟགས་མེད་པར་ཡང་མི་རིགས་སོ། ། གལ་ཏེ་བློ་དེས་གཟུགས་འཛིན་ན། ། རང་གི་རང་བཞིན་ལ་འཛིན་འགྱུར། ། རྐྱེན་ལས་སྐྱེས་པས་ཡོད་མིན་པས། ། ཡང་དག་གཟུགས་མེད་ཇི་ལྟར་འཛིན། ། ཇི་སྐད་བཤད་གཟུགས་སྐྱེས་པའི་བློའི། ། སྐད་ཅིག་སྐད་ཅིག་གིས་མི་འཛིན། ། འདས་དང་མ་འོངས་གཟུགས་ཀྱི་ནི། ། དེ་ཡིས་ཇི་ལྟར་རྟོགས་པར་འགྱུར། ། གང་ཚེ་ནམ་ཡང་ཁ་དོག་དང་། ། དབྱིབས་དག་ཐ་དད་ཉིད་མེད་པས། ། དེ་དག་ཐ་དད་འཛིན་ཡོད་མིན། ། གཟུགས་དེ་གཅིག་ཏུའང་གྲགས་པ་མིན། ། མིག་བློ་མིག་ལ་ཡོད་མིན་ཏེ། ། གཟུགས་ལ་ཡོད་མིན་བར་ན��མེད། ། གཟུགས་དང་མིག་ལ་བརྟེན་ནས་དེ། ། ཡོངས་སུ་རྟོག་པ་ལོག་པ་ཡིན། ། གལ་ཏེ་མིག་བདག་མིག་མཐོང་ན། ། དེ་གཟུགས་མཐོང་བར་ཇི་ལྟར་འགྱུར། ། དེ་ཕྱིར་མིག་དང་གཟུགས་བདག་མེད། ། སྐྱེ་མཆེད་ལྷག་མའང་དེ་བཞིན་ནོ། ། མིག་ནི་རང་བདག་ཉིད་ཀྱིས་སྟོང་། ། དེ་ནི་གཞན་བདག་གིས་ཀྱང་སྟོང་། ། གཟུགས་ཀྱང་དེ་བཞིན་སྟོང་པ་སྟེ། ། སྐྱེ་མཆེད་ལྷག་མའང་དེ་བཞིན་ནོ། ། གང་ཚེ་གཅིག་རེག་ལྷན་ཅིག་འགྱུར། ། དེ་ཚེ་གཞན་རྣམས་སྟོང་པ་ཉིད། ། སྟོང་པའམ་མི་སྟོང་མི་སྟོན་ལ། ། མི་སྟོང་པ་ཡང་རྟེན་མི་བརྟེན། ། ངོ་བོ་མི་གནས་ཡོད་མིན་པས། ། གསུམ་འདུས་པ་ཡོད་མ་ཡིན་ནོ། ། དེ་བདག་ཉིད་ཀྱིས་རེག་མེད་པས། ། དེ་ཚེ་ཚོར་བ་ཡོད་མ་ཡིན། ། ནང་དང་ཕྱི་ཡི་སྐྱེ་མཆེད་ལ། ། བརྟེན་ནས་རྣམ་པར་ཤེས་པ་འབྱུང་། ། དེ་ལྟ་བས་ན་རྣམ་ཤེས་ནི། ། སྨིག་རྒྱུ་སྒྱུ་མ་བཞིན་དུ་སྟོང་། ། རྣམ་ཤེས་ཤེས་བྱ་ལ་བརྟེན་ནས། ། འབྱུང་ལ་ཤེས་བྱ་ཡོད་མ་ཡིན། ། ཤེས་བྱ་ཤེས་པ་མེད་པའི་ཕྱིར། ། དེ་ཕྱིར་ཤེས་པ་པོ་ཉིད་མེད། ། ཐམས་ཅད་ ༼༦༽
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+བྱས་པ་ཞེས་བྱ་བ། སློབ་དཔོན་འཕགས་པ་ཀླུ་སྒྲུབ་ཀྱིས་མཛད་པ་རྫོགས་སོ། ། ། །ལོ་ཙྪ་བ་གཞོན་ནུ་མཆོག་དང་། སྙན་དར་མ [/INST] {"spans": []}</s>
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-100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, 8853, 1028, 550, 1115, 5159, 29913, 2][INFO|configuration_utils.py:765] 2026-06-18 08:56:54,098 >> loading configuration file config.json from cache at /root/.cache/huggingface/hub/models--YoLo2000--TiLamb-7B/snapshots/9e9426a248492fd02abfbd21d13f000456408bde/config.json
+[INFO|configuration_utils.py:839] 2026-06-18 08:56:54,100 >> Model config LlamaConfig {
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": 1,
+  "dtype": "float16",
+  "eos_token_id": 2,
+  "head_dim": 128,
+  "hidden_act": "silu",
+  "hidden_size": 4096,
+  "initializer_range": 0.02,
+  "intermediate_size": 11008,
+  "max_position_embeddings": 4096,
+  "mlp_bias": false,
+  "model_type": "llama",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 32,
+  "num_key_value_heads": 32,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-05,
+  "rope_scaling": null,
+  "rope_theta": 10000.0,
+  "tie_word_embeddings": false,
+  "transformers_version": "4.56.2",
+  "use_cache": true,
+  "vocab_size": 61221
+}
+
+
+labels:
+{"spans": []}</s>
+[INFO|2026-06-18 08:56:54] llamafactory.model.model_utils.kv_cache:144 >> KV cache is disabled during training.
+[WARNING|logging.py:328] 2026-06-18 08:56:54,213 >> `torch_dtype` is deprecated! Use `dtype` instead!
+[INFO|modeling_utils.py:1280] 2026-06-18 08:56:54,350 >> loading weights file pytorch_model.bin from cache at /root/.cache/huggingface/hub/models--YoLo2000--TiLamb-7B/snapshots/9e9426a248492fd02abfbd21d13f000456408bde/pytorch_model.bin.index.json
+[INFO|modeling_utils.py:1351] 2026-06-18 08:56:54,351 >> Will use dtype=torch.float16 as defined in model's config object
+[INFO|modeling_utils.py:2466] 2026-06-18 08:56:54,351 >> Instantiating LlamaForCausalLM model under default dtype torch.float16.
+[INFO|configuration_utils.py:1055] 2026-06-18 08:56:54,354 >> Generate config GenerationConfig {
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "use_cache": false
+}
+
+
Loading checkpoint shards:   0%|          | 0/2 [00:00<?, ?it/s][INFO|safetensors_conversion.py:61] 2026-06-18 08:56:54,537 >> Attempting to create safetensors variant
+[INFO|safetensors_conversion.py:74] 2026-06-18 08:56:55,041 >> Safetensors PR exists
+
Loading checkpoint shards:  50%|█████     | 1/2 [00:01<00:00,  1.00it/s]
Loading checkpoint shards: 100%|██████████| 2/2 [00:01<00:00,  1.16it/s]
Loading checkpoint shards: 100%|██████████| 2/2 [00:01<00:00,  1.14it/s]
+[INFO|modeling_utils.py:5724] 2026-06-18 08:56:56,276 >> All model checkpoint weights were used when initializing LlamaForCausalLM.
+
+[INFO|modeling_utils.py:5732] 2026-06-18 08:56:56,276 >> All the weights of LlamaForCausalLM were initialized from the model checkpoint at YoLo2000/TiLamb-7B.
+If your task is similar to the task the model of the checkpoint was trained on, you can already use LlamaForCausalLM for predictions without further training.
+[INFO|configuration_utils.py:1010] 2026-06-18 08:56:56,495 >> loading configuration file generation_config.json from cache at /root/.cache/huggingface/hub/models--YoLo2000--TiLamb-7B/snapshots/9e9426a248492fd02abfbd21d13f000456408bde/generation_config.json
+[INFO|configuration_utils.py:1055] 2026-06-18 08:56:56,496 >> Generate config GenerationConfig {
+  "bos_token_id": 1,
+  "do_sample": true,
+  "eos_token_id": 2,
+  "max_length": 4096,
+  "pad_token_id": 0,
+  "temperature": 0.6,
+  "top_p": 0.9
+}
+
+[INFO|2026-06-18 08:56:56] llamafactory.model.model_utils.checkpointing:144 >> Gradient checkpointing enabled.
+[INFO|2026-06-18 08:56:56] llamafactory.model.model_utils.attention:144 >> Using torch SDPA for faster training and inference.
+[INFO|2026-06-18 08:56:56] llamafactory.model.adapter:144 >> Upcasting trainable params to float32.
+[INFO|2026-06-18 08:56:56] llamafactory.model.adapter:144 >> Fine-tuning method: LoRA
+[INFO|2026-06-18 08:56:56] llamafactory.model.model_utils.misc:144 >> Found linear modules: q_proj,gate_proj,up_proj,o_proj,down_proj,k_proj,v_proj
+[INFO|2026-06-18 08:56:57] llamafactory.model.loader:144 >> trainable params: 39,976,960 || all params: 7,017,771,008 || trainable%: 0.5697
+[INFO|trainer.py:757] 2026-06-18 08:56:57,137 >> Using auto half precision backend
+[WARNING|trainer.py:985] 2026-06-18 08:56:57,137 >> The tokenizer has new PAD/BOS/EOS tokens that differ from the model config and generation config. The model config and generation config were aligned accordingly, being updated with the tokenizer's values. Updated tokens: {'pad_token_id': 2}.
+[INFO|trainer.py:2523] 2026-06-18 08:56:57,356 >> ***** Running training *****
+[INFO|trainer.py:2524] 2026-06-18 08:56:57,356 >>   Num examples = 6,035
+[INFO|trainer.py:2525] 2026-06-18 08:56:57,356 >>   Num Epochs = 1
+[INFO|trainer.py:2526] 2026-06-18 08:56:57,356 >>   Instantaneous batch size per device = 1
+[INFO|trainer.py:2529] 2026-06-18 08:56:57,356 >>   Total train batch size (w. parallel, distributed & accumulation) = 16
+[INFO|trainer.py:2530] 2026-06-18 08:56:57,356 >>   Gradient Accumulation steps = 16
+[INFO|trainer.py:2531] 2026-06-18 08:56:57,356 >>   Total optimization steps = 378
+[INFO|trainer.py:2532] 2026-06-18 08:56:57,358 >>   Number of trainable parameters = 39,976,960
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+***** Running Evaluation *****
+[INFO|trainer.py:4625] 2026-06-18 10:23:17,850 >>   Num examples = 100
+[INFO|trainer.py:4628] 2026-06-18 10:23:17,850 >>   Batch size = 1
+{'loss': 6.2444, 'grad_norm': 9.946784019470215, 'learning_rate': 0.00015000000000000001, 'epoch': 0.03}
+{'loss': 1.1512, 'grad_norm': 4.464430809020996, 'learning_rate': 0.00019981954330597143, 'epoch': 0.05}
+{'loss': 0.5421, 'grad_norm': 1.799384355545044, 'learning_rate': 0.00019893724130196828, 'epoch': 0.08}
+{'loss': 0.4576, 'grad_norm': 1.8336181640625, 'learning_rate': 0.00019732643737003827, 'epoch': 0.11}
+{'loss': 0.4113, 'grad_norm': 1.2008732557296753, 'learning_rate': 0.00019499899229945012, 'epoch': 0.13}
+{'loss': 0.3787, 'grad_norm': 1.3873170614242554, 'learning_rate': 0.00019197204370389467, 'epoch': 0.16}
+{'loss': 0.3475, 'grad_norm': 0.8817585706710815, 'learning_rate': 0.00018826787983255473, 'epoch': 0.19}
+{'loss': 0.3518, 'grad_norm': 1.0500197410583496, 'learning_rate': 0.00018391377545563938, 'epoch': 0.21}
+{'loss': 0.3404, 'grad_norm': 0.6465247869491577, 'learning_rate': 0.00017894179103280198, 'epoch': 0.24}
+{'loss': 0.3454, 'grad_norm': 0.9379073977470398, 'learning_rate': 0.00017338853664321992, 'epoch': 0.27}
+{'loss': 0.3194, 'grad_norm': 0.8305555582046509, 'learning_rate': 0.0001672949024155833, 'epoch': 0.29}
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+{'loss': 0.2524, 'grad_norm': 0.4572385549545288, 'learning_rate': 9.656723994867566e-05, 'epoch': 0.53}
+
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+
                                                 

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                                                 [INFO|trainer.py:4289] 2026-06-18 10:24:02,840 >> Saving model checkpoint to saves/tibetan-title-lora-pilot/checkpoint-200
+[INFO|configuration_utils.py:765] 2026-06-18 10:24:03,192 >> loading configuration file config.json from cache at /root/.cache/huggingface/hub/models--YoLo2000--TiLamb-7B/snapshots/9e9426a248492fd02abfbd21d13f000456408bde/config.json
+[INFO|configuration_utils.py:839] 2026-06-18 10:24:03,194 >> Model config LlamaConfig {
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": 1,
+  "dtype": "float16",
+  "eos_token_id": 2,
+  "head_dim": 128,
+  "hidden_act": "silu",
+  "hidden_size": 4096,
+  "initializer_range": 0.02,
+  "intermediate_size": 11008,
+  "max_position_embeddings": 4096,
+  "mlp_bias": false,
+  "model_type": "llama",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 32,
+  "num_key_value_heads": 32,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-05,
+  "rope_scaling": null,
+  "rope_theta": 10000.0,
+  "tie_word_embeddings": false,
+  "transformers_version": "4.56.2",
+  "use_cache": true,
+  "vocab_size": 61221
+}
+
+[INFO|tokenization_utils_base.py:2394] 2026-06-18 10:24:03,454 >> chat template saved in saves/tibetan-title-lora-pilot/checkpoint-200/chat_template.jinja
+[INFO|tokenization_utils_base.py:2563] 2026-06-18 10:24:03,454 >> tokenizer config file saved in saves/tibetan-title-lora-pilot/checkpoint-200/tokenizer_config.json
+[INFO|tokenization_utils_base.py:2572] 2026-06-18 10:24:03,454 >> Special tokens file saved in saves/tibetan-title-lora-pilot/checkpoint-200/special_tokens_map.json
+
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