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[09:10:27] config {'DATASET': 'staged', 'EPOCHS': 40.0, 'MODEL_REPO': 'smjain/sap-archgen-lfm2-230M', 'GGUF_REPO': 'smjain/sap-archgen-lfm2-230M-GGUF', 'GGUF_FILE': 'sap-archgen-lfm2-230M-Q4_0.gguf'}
/usr/local/lib/python3.11/dist-packages/huggingface_hub/constants.py:298: FutureWarning: The `HF_HUB_ENABLE_HF_TRANSFER` environment variable is deprecated as 'hf_transfer' is not used anymore. Please use `HF_XET_HIGH_PERFORMANCE` instead to enable high performance transfer with Xet. Visit https://huggingface.co/docs/huggingface_hub/package_reference/environment_variables#hfxethighperformance for more details.
 warnings.warn(
🦥 Unsloth: Will patch your computer to enable 2x faster free finetuning.
🦥 Unsloth Zoo will now patch everything to make training faster!
[09:10:37] loading unsloth/LFM2.5-230M
==((====))== Unsloth 2026.6.9: Fast Lfm2 patching. Transformers: 5.5.0.
 \\ /| NVIDIA A100 80GB PCIe. Num GPUs = 1. Max memory: 79.25 GB. Platform: Linux.
O^O/ \_/ \ Torch: 2.10.0+cu128. CUDA: 8.0. CUDA Toolkit: 12.8. Triton: 3.6.0
\ / Bfloat16 = TRUE. FA [Xformers = 0.0.35. FA2 = False]
 "-____-" Free license: http://github.com/unslothai/unsloth
Unsloth: Fast downloading is enabled - ignore downloading bars which are red colored!
Unsloth: QLoRA and full finetuning all not selected. Switching to 16bit LoRA.
 Loading weights: 0%| | 0/132 [00:00<?, ?it/s] Loading weights: 100%|██████████| 132/132 [00:00<00:00, 3371.61it/s]
[09:10:57] loaded unsloth/LFM2.5-230M
Unsloth: Explicit target_modules are constrained by the finetune_(vision|language|attention|mlp) filters; adapters attach only where both select.
 Generating train split: 0 examples [00:00, ? examples/s] Generating train split: 507 examples [00:00, 71802.81 examples/s]
[09:10:59] train rows 507 from dataset/train_staged.jsonl
 Map: 0%| | 0/507 [00:00<?, ? examples/s] Map: 67%|██████▋ | 341/507 [00:00<00:00, 3378.96 examples/s] Map: 100%|██████████| 507/507 [00:00<00:00, 3264.02 examples/s]
warmup_ratio is deprecated and will be removed in v5.2. Use `warmup_steps` instead.
 Unsloth: Tokenizing ["text"] (num_proc=64): 0%| | 0/507 [00:00<?, ? examples/s] Unsloth: Tokenizing ["text"] (num_proc=64): 2%|▏ | 8/507 [00:02<02:11, 3.79 examples/s] Unsloth: Tokenizing ["text"] (num_proc=64): 5%|▍ | 24/507 [00:02<00:35, 13.58 examples/s] Unsloth: Tokenizing ["text"] (num_proc=64): 8%|▊ | 40/507 [00:02<00:18, 25.56 examples/s] Unsloth: Tokenizing ["text"] (num_proc=64): 13%|█▎ | 64/507 [00:02<00:09, 45.41 examples/s] Unsloth: Tokenizing ["text"] (num_proc=64): 19%|█▉ | 96/507 [00:02<00:05, 73.17 examples/s] Unsloth: Tokenizing ["text"] (num_proc=64): 24%|██▎ | 120/507 [00:02<00:04, 95.27 examples/s] Unsloth: Tokenizing ["text"] (num_proc=64): 28%|██▊ | 144/507 [00:02<00:03, 111.95 examples/s] Unsloth: Tokenizing ["text"] (num_proc=64): 33%|███▎ | 168/507 [00:03<00:02, 124.01 examples/s] Unsloth: Tokenizing ["text"] (num_proc=64): 38%|███▊ | 192/507 [00:03<00:02, 137.83 examples/s] Unsloth: Tokenizing ["text"] (num_proc=64): 43%|████▎ | 216/507 [00:03<00:02, 136.53 examples/s] Unsloth: Tokenizing ["text"] (num_proc=64): 49%|████▉ | 248/507 [00:03<00:01, 160.09 examples/s] Unsloth: Tokenizing ["text"] (num_proc=64): 54%|█████▎ | 272/507 [00:03<00:01, 164.81 examples/s] Unsloth: Tokenizing ["text"] (num_proc=64): 58%|█████▊ | 296/507 [00:03<00:01, 160.92 examples/s] Unsloth: Tokenizing ["text"] (num_proc=64): 63%|██████▎ | 320/507 [00:03<00:01, 167.46 examples/s] Unsloth: Tokenizing ["text"] (num_proc=64): 68%|██████▊ | 344/507 [00:04<00:01, 159.34 examples/s] Unsloth: Tokenizing ["text"] (num_proc=64): 73%|███████▎ | 368/507 [00:04<00:00, 164.31 examples/s] Unsloth: Tokenizing ["text"] (num_proc=64): 77%|███████▋ | 392/507 [00:04<00:00, 175.77 examples/s] Unsloth: Tokenizing ["text"] (num_proc=64): 82%|████████▏ | 416/507 [00:04<00:00, 163.05 examples/s] Unsloth: Tokenizing ["text"] (num_proc=64): 87%|████████▋ | 440/507 [00:04<00:00, 175.69 examples/s] Unsloth: Tokenizing ["text"] (num_proc=64): 92%|█████████▏| 464/507 [00:04<00:00, 180.20 examples/s] Unsloth: Tokenizing ["text"] (num_proc=64): 96%|█████████▌| 486/507 [00:04<00:00, 179.05 examples/s] Unsloth: Tokenizing ["text"] (num_proc=64): 100%|██████████| 507/507 [00:05<00:00, 171.25 examples/s] Unsloth: Tokenizing ["text"] (num_proc=64): 100%|██████████| 507/507 [00:05<00:00, 86.45 examples/s]
🦥 Unsloth: Padding-free auto-enabled, enabling faster training.
 Map (num_proc=64): 0%| | 0/507 [00:00<?, ? examples/s] Map (num_proc=64): 2%|▏ | 8/507 [00:02<02:31, 3.29 examples/s] Map (num_proc=64): 39%|███▉ | 200/507 [00:02<00:02, 109.31 examples/s] Map (num_proc=64): 100%|██████████| 507/507 [00:03<00:00, 154.01 examples/s]
 Filter (num_proc=64): 0%| | 0/507 [00:00<?, ? examples/s] Filter (num_proc=64): 2%|▏ | 8/507 [00:02<02:28, 3.36 examples/s] Filter (num_proc=64): 35%|███▍ | 176/507 [00:02<00:03, 98.09 examples/s] Filter (num_proc=64): 100%|██████████| 507/507 [00:03<00:00, 161.82 examples/s]
[09:11:12] responses-only masking on
[09:11:12] === train ===
==((====))== Unsloth - 2x faster free finetuning | Num GPUs used = 1
 \\ /| Num examples = 507 | Num Epochs = 40 | Total steps = 2,560
O^O/ \_/ \ Batch size per device = 2 | Gradient accumulation steps = 4
\ / Data Parallel GPUs = 1 | Total batch size (2 x 4 x 1) = 8
 "-____-" Trainable parameters = 983,040 of 230,676,224 (0.43% trained)
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Unsloth: Double buffering enabled (parallel H2D + compute) for backward pass.
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{'loss': '0.002562', 'grad_norm': '0.07407', 'learning_rate': '0.0001539', 'epoch': '14.13'}
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{'loss': '0.008644', 'grad_norm': '0.209', 'learning_rate': '0.0001535', 'epoch': '14.19'}
{'loss': '0.001976', 'grad_norm': '0.03682', 'learning_rate': '0.0001533', 'epoch': '14.22'}
{'loss': '0.002587', 'grad_norm': '0.02552', 'learning_rate': '0.0001531', 'epoch': '14.25'}
{'loss': '0.005058', 'grad_norm': '0.0553', 'learning_rate': '0.0001528', 'epoch': '14.28'}
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{'loss': '0.001429', 'grad_norm': '0.0593', 'learning_rate': '0.000112', 'epoch': '19.57'}
{'loss': '0.003156', 'grad_norm': '0.1036', 'learning_rate': '0.0001117', 'epoch': '19.6'}
{'loss': '0.00226', 'grad_norm': '0.04847', 'learning_rate': '0.0001115', 'epoch': '19.63'}
{'loss': '0.001572', 'grad_norm': '0.06071', 'learning_rate': '0.0001112', 'epoch': '19.66'}
{'loss': '0.002528', 'grad_norm': '0.02753', 'learning_rate': '0.000111', 'epoch': '19.69'}
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{'loss': '0.001432', 'grad_norm': '0.0209', 'learning_rate': '4.477e-05', 'epoch': '28.09'}
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{'loss': '0.001359', 'grad_norm': '0.01836', 'learning_rate': '2.74e-05', 'epoch': '30.85'} 77%|███████▋ | 1974/2560 [09:19<02:36, 3.75it/s] 77%|███████▋ | 1975/2560 [09:19<02:36, 3.74it/s] 77%|███████▋ | 1976/2560 [09:20<02:36, 3.73it/s] 77%|███████▋ | 1976/2560 [09:20<02:36, 3.73it/s] 77%|███████▋ | 1977/2560 [09:20<02:36, 3.72it/s] 77%|███████▋ | 1978/2560 [09:20<02:35, 3.74it/s] 77%|███████▋ | 1978/2560 [09:20<02:35, 3.74it/s] 77%|███████▋ | 1979/2560 [09:20<02:34, 3.77it/s] 77%|███████▋ | 1980/2560 [09:21<02:32, 3.79it/s] 77%|███████▋ | 1980/2560 [09:21<02:32, 3.79it/s] 77%|███████▋ | 1981/2560 [09:21<02:32, 3.80it/s] 77%|███████▋ | 1982/2560 [09:21<02:32, 3.78it/s] 77%|███████▋ | 1982/2560 [09:21<02:32, 3.78it/s] 77%|███████▋ | 1983/2560 [09:21<02:33, 3.76it/s] 78%|███████▊ | 1984/2560 [09:22<02:10, 4.43it/s] 78%|███████▊ | 1984/2560 [09:22<02:10, 4.43it/s] 78%|███████▊ | 1985/2560 [09:22<02:17, 4.18it/s] 78%|███████▊ | 1986/2560 [09:22<02:22, 4.04it/s] 78%|███████▊ | 1986/2560 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{'loss': '0.001372', 'grad_norm': '0.02578', 'learning_rate': '2.343e-07', 'epoch': '39.19'} 98%|█████████▊| 2508/2560 [11:43<00:13, 3.84it/s] 98%|█████████▊| 2509/2560 [11:43<00:13, 3.85it/s] 98%|█████████▊| 2510/2560 [11:43<00:12, 3.85it/s] 98%|█████████▊| 2510/2560 [11:43<00:12, 3.85it/s] 98%|█████████▊| 2511/2560 [11:43<00:12, 3.85it/s] 98%|█████████▊| 2512/2560 [11:44<00:12, 3.87it/s] 98%|█████████▊| 2512/2560 [11:44<00:12, 3.87it/s] 98%|█████████▊| 2513/2560 [11:44<00:12, 3.87it/s] 98%|█████████▊| 2514/2560 [11:44<00:11, 3.89it/s] 98%|█████████▊| 2514/2560 [11:44<00:11, 3.89it/s] 98%|█████████▊| 2515/2560 [11:44<00:11, 3.89it/s] 98%|█████████▊| 2516/2560 [11:45<00:11, 3.89it/s] 98%|█████████▊| 2516/2560 [11:45<00:11, 3.89it/s] 98%|█████████▊| 2517/2560 [11:45<00:11, 3.89it/s] 98%|█████████▊| 2518/2560 [11:45<00:10, 3.89it/s] 98%|█████████▊| 2518/2560 [11:45<00:10, 3.89it/s] 98%|█████████▊| 2519/2560 [11:45<00:10, 3.88it/s] 98%|█████████▊| 2520/2560 [11:46<00:10, 3.86it/s] 98%|█████████▊| 2520/2560 [11:46<00:10, 3.86it/s] 98%|█████████▊| 2521/2560 [11:46<00:10, 3.88it/s] 99%|█████████▊| 2522/2560 [11:46<00:09, 3.88it/s] 99%|█████████▊| 2522/2560 [11:46<00:09, 3.88it/s] 99%|█████████▊| 2523/2560 [11:47<00:09, 3.87it/s] 99%|█████████▊| 2524/2560 [11:47<00:09, 3.87it/s] 99%|█████████▊| 2524/2560 [11:47<00:09, 3.87it/s] 99%|█████████▊| 2525/2560 [11:47<00:09, 3.86it/s] 99%|█████████▊| 2526/2560 [11:47<00:08, 3.88it/s] 99%|█████████▊| 2526/2560 [11:47<00:08, 3.88it/s] 99%|█████████▊| 2527/2560 [11:48<00:08, 3.88it/s] 99%|█████████▉| 2528/2560 [11:48<00:08, 3.88it/s] 99%|█████████▉| 2528/2560 [11:48<00:08, 3.88it/s] 99%|█████████▉| 2529/2560 [11:48<00:07, 3.88it/s] 99%|█████████▉| 2530/2560 [11:48<00:07, 3.87it/s] 99%|█████████▉| 2530/2560 [11:48<00:07, 3.87it/s] 99%|█████████▉| 2531/2560 [11:49<00:07, 3.88it/s] 99%|█████████▉| 2532/2560 [11:49<00:07, 3.87it/s] 99%|█████████▉| 2532/2560 [11:49<00:07, 3.87it/s] 99%|█████████▉| 2533/2560 [11:49<00:07, 3.86it/s] 99%|█████████▉| 2534/2560 [11:49<00:06, 3.85it/s] 99%|█████████▉| 2534/2560 [11:49<00:06, 3.85it/s] 99%|█████████▉| 2535/2560 [11:50<00:06, 3.82it/s] 99%|█████████▉| 2536/2560 [11:50<00:06, 3.76it/s] 99%|█████████▉| 2536/2560 [11:50<00:06, 3.76it/s] 99%|█████████▉| 2537/2560 [11:50<00:06, 3.72it/s] 99%|█████████▉| 2538/2560 [11:50<00:06, 3.62it/s] 99%|█████████▉| 2538/2560 [11:50<00:06, 3.62it/s] 99%|█████████▉| 2539/2560 [11:51<00:05, 3.60it/s] 99%|█████████▉| 2540/2560 [11:51<00:05, 3.52it/s] 99%|█████████▉| 2540/2560 [11:51<00:05, 3.52it/s] 99%|█████████▉| 2541/2560 [11:51<00:05, 3.45it/s] 99%|█████████▉| 2542/2560 [11:52<00:05, 3.41it/s] 99%|█████████▉| 2542/2560 [11:52<00:05, 3.41it/s] 99%|█████████▉| 2543/2560 [11:52<00:05, 3.39it/s] 99%|█████████▉| 2544/2560 [11:52<00:04, 3.42it/s] 99%|█████████▉| 2544/2560 [11:52<00:04, 3.42it/s] 99%|█████████▉| 2545/2560 [11:53<00:04, 3.48it/s] 99%|█████████▉| 2546/2560 [11:53<00:03, 3.53it/s] 99%|█████████▉| 2546/2560 [11:53<00:03, 3.53it/s] 99%|█████████▉| 2547/2560 [11:53<00:03, 3.59it/s] 100%|█████████▉| 2548/2560 [11:53<00:03, 3.62it/s] 100%|█████████▉| 2548/2560 [11:53<00:03, 3.62it/s] 100%|█████████▉| 2549/2560 [11:54<00:03, 3.66it/s] 100%|█████████▉| 2550/2560 [11:54<00:02, 3.70it/s] 100%|█████████▉| 2550/2560 [11:54<00:02, 3.70it/s] 100%|█████████▉| 2551/2560 [11:54<00:02, 3.71it/s] 100%|█████████▉| 2552/2560 [11:54<00:02, 3.72it/s] 100%|█████████▉| 2552/2560 [11:54<00:02, 3.72it/s] 100%|█████████▉| 2553/2560 [11:55<00:01, 3.75it/s] 100%|█████████▉| 2554/2560 [11:55<00:01, 3.72it/s] 100%|█████████▉| 2554/2560 [11:55<00:01, 3.72it/s] 100%|█████████▉| 2555/2560 [11:55<00:01, 3.75it/s] 100%|█████████▉| 2556/2560 [11:55<00:01, 3.75it/s] 100%|█████████▉| 2556/2560 [11:55<00:01, 3.75it/s] 100%|█████████▉| 2557/2560 [11:56<00:00, 3.75it/s] 100%|█████████▉| 2558/2560 [11:56<00:00, 3.70it/s] 100%|█████████▉| 2558/2560 [11:56<00:00, 3.70it/s] 100%|█████████▉| 2559/2560 [11:56<00:00, 3.72it/s] 100%|██████████| 2560/2560 [11:56<00:00, 4.37it/s] 100%|██████████| 2560/2560 [11:56<00:00, 4.37it/s] 100%|██████████| 2560/2560 [11:56<00:00, 4.37it/s] 100%|██████████| 2560/2560 [11:56<00:00, 3.57it/s]
{'loss': '0.001541', 'grad_norm': '0.02468', 'learning_rate': '2.169e-07', 'epoch': '39.22'}
{'loss': '0.001296', 'grad_norm': '0.02509', 'learning_rate': '2.003e-07', 'epoch': '39.25'}
{'loss': '0.001649', 'grad_norm': '0.06117', 'learning_rate': '1.842e-07', 'epoch': '39.28'}
{'loss': '0.001109', 'grad_norm': '0.04072', 'learning_rate': '1.689e-07', 'epoch': '39.31'}
{'loss': '0.001157', 'grad_norm': '0.0288', 'learning_rate': '1.542e-07', 'epoch': '39.35'}
{'loss': '0.001781', 'grad_norm': '0.02883', 'learning_rate': '1.402e-07', 'epoch': '39.38'}
{'loss': '0.001371', 'grad_norm': '0.02568', 'learning_rate': '1.269e-07', 'epoch': '39.41'}
{'loss': '0.001522', 'grad_norm': '0.03333', 'learning_rate': '1.142e-07', 'epoch': '39.44'}
{'loss': '0.001768', 'grad_norm': '0.01818', 'learning_rate': '1.022e-07', 'epoch': '39.47'}
{'loss': '0.002008', 'grad_norm': '0.04948', 'learning_rate': '9.085e-08', 'epoch': '39.5'}
{'loss': '0.001759', 'grad_norm': '0.02312', 'learning_rate': '8.017e-08', 'epoch': '39.54'}
{'loss': '0.001473', 'grad_norm': '0.01943', 'learning_rate': '7.016e-08', 'epoch': '39.57'}
{'loss': '0.001282', 'grad_norm': '0.02912', 'learning_rate': '6.082e-08', 'epoch': '39.6'}
{'loss': '0.001245', 'grad_norm': '0.05375', 'learning_rate': '5.214e-08', 'epoch': '39.63'}
{'loss': '0.001477', 'grad_norm': '0.0324', 'learning_rate': '4.413e-08', 'epoch': '39.66'}
{'loss': '0.001644', 'grad_norm': '0.03436', 'learning_rate': '3.679e-08', 'epoch': '39.69'}
{'loss': '0.001172', 'grad_norm': '0.02185', 'learning_rate': '3.012e-08', 'epoch': '39.72'}
{'loss': '0.001682', 'grad_norm': '0.02014', 'learning_rate': '2.411e-08', 'epoch': '39.76'}
{'loss': '0.001191', 'grad_norm': '0.02827', 'learning_rate': '1.877e-08', 'epoch': '39.79'}
{'loss': '0.001468', 'grad_norm': '0.02136', 'learning_rate': '1.41e-08', 'epoch': '39.82'}
{'loss': '0.001442', 'grad_norm': '0.02254', 'learning_rate': '1.01e-08', 'epoch': '39.85'}
{'loss': '0.001717', 'grad_norm': '0.02532', 'learning_rate': '6.758e-09', 'epoch': '39.88'}
{'loss': '0.001591', 'grad_norm': '0.01641', 'learning_rate': '4.088e-09', 'epoch': '39.91'}
{'loss': '0.001323', 'grad_norm': '0.0197', 'learning_rate': '2.086e-09', 'epoch': '39.94'}
{'loss': '0.001325', 'grad_norm': '0.02043', 'learning_rate': '7.509e-10', 'epoch': '39.98'}
{'loss': '0.001289', 'grad_norm': '0.04457', 'learning_rate': '8.343e-11', 'epoch': '40'}
{'train_runtime': '716.9', 'train_samples_per_second': '28.29', 'train_steps_per_second': '3.571', 'train_loss': '0.03738', 'epoch': '40'}
[09:23:11] === done ===
The attention mask is not set and cannot be inferred from input because pad token is same as eos token. As a consequence, you may observe unexpected behavior. Please pass your input's `attention_mask` to obtain reliable results.
Both `max_new_tokens` (=1600) and `max_length`(=128000) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)
[09:23:19] stage1 blocks: 3
Both `max_new_tokens` (=1600) and `max_length`(=128000) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)
[09:23:23] stage2 components
Both `max_new_tokens` (=1600) and `max_length`(=128000) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)
[09:23:26] stage3 connections: 12
[09:23:26] verify round 1 issues: ["2 unconnected component(s) ['c3', 'c1']: wire each into the flow", 'under-connected: 12 connections for 15 components (expect >= 14)', "duplicate service(s) ['SAP Destination service']: wire the existing one, do NOT add duplicate services"]
Both `max_new_tokens` (=1600) and `max_length`(=128000) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)
[09:23:35] verify round 2 issues: ["2 unconnected component(s) ['c3', 'c1']: wire each into the flow", 'under-connected: 13 connections for 15 components (expect >= 14)', "duplicate component id(s) ['c12', 'c13']: each component must appear once"]
Both `max_new_tokens` (=1600) and `max_length`(=128000) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)
[09:23:44] final issues: ["2 unconnected component(s) ['c3', 'c1']: wire each into the flow", 'under-connected: 13 connections for 15 components (expect >= 14)', "duplicate component id(s) ['c12', 'c13']: each component must appear once", "duplicate service(s) ['SAP Destination service']: wire the existing one, do NOT add duplicate services", 'Cloud Connector present but no SAP Connectivity service (incomplete on-prem tunnel).']
[09:23:44] EVAL {'arch': 'Procurement copilot (novel)', 'ok': True, 'blocks': 6, 'components': 17, 'connections': 13, 'verify_rounds': 2, 'remaining_issues': ["2 unconnected component(s) ['c3', 'c1']: wire each into the flow", 'under-connected: 13 connections for 15 components (expect >= 14)', "duplicate component id(s) ['c12', 'c13']: each component must appear once", "duplicate service(s) ['SAP Destination service']: wire the existing one, do NOT add duplicate services", 'Cloud Connector present but no SAP Connectivity service (incomplete on-prem tunnel).'], 'info': '24 nodes, 13 edges'}
Both `max_new_tokens` (=1600) and `max_length`(=128000) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)
[09:23:46] stage1 blocks: 3
Both `max_new_tokens` (=1600) and `max_length`(=128000) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)
[09:23:48] stage2 components
Both `max_new_tokens` (=1600) and `max_length`(=128000) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)
[09:23:50] stage3 connections: 9
[09:23:50] final issues: []
[09:23:50] EVAL {'arch': 'Predictive maintenance (novel)', 'ok': True, 'blocks': 5, 'components': 10, 'connections': 9, 'verify_rounds': 0, 'remaining_issues': [], 'info': '16 nodes, 9 edges'}
Both `max_new_tokens` (=1600) and `max_length`(=128000) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)
[09:23:50] stage1 blocks: 0
Both `max_new_tokens` (=1600) and `max_length`(=128000) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)
[09:23:52] stage2 components
Both `max_new_tokens` (=1600) and `max_length`(=128000) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)
[09:23:52] stage3 connections: 2
[09:23:52] verify round 1 issues: ['fewer than 2 components placed', 'connection c0->c1 references missing component', 'connection c1->c0 references missing component']
Both `max_new_tokens` (=1600) and `max_length`(=128000) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)
[09:23:58] verify round 2 issues: ['fewer than 2 components placed', 'connection c0->c1 references missing component', 'connection c1->c0 references missing component']
Both `max_new_tokens` (=1600) and `max_length`(=128000) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)
[09:24:04] final issues: ['fewer than 2 components placed', 'connection c0->c1 references missing component', 'connection c1->c0 references missing component', 'does not render: 1 nodes, 0 edges']
[09:24:04] EVAL {'arch': 'Claims handling RAG (held-out domain)', 'ok': False, 'blocks': 0, 'components': 0, 'connections': 2, 'verify_rounds': 2, 'remaining_issues': ['fewer than 2 components placed', 'connection c0->c1 references missing component', 'connection c1->c0 references missing component', 'does not render: 1 nodes, 0 edges'], 'info': '1 nodes, 0 edges'}
Both `max_new_tokens` (=1600) and `max_length`(=128000) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)
[09:24:06] stage1 blocks: 3
Both `max_new_tokens` (=1600) and `max_length`(=128000) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)
[09:24:09] stage2 components
Both `max_new_tokens` (=1600) and `max_length`(=128000) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)
[09:24:10] stage3 connections: 7
[09:24:10] final issues: []
[09:24:10] EVAL {'arch': 'Asset management events (held-out domain)', 'ok': True, 'blocks': 5, 'components': 8, 'connections': 7, 'verify_rounds': 0, 'remaining_issues': [], 'info': '14 nodes, 7 edges'}
Both `max_new_tokens` (=1600) and `max_length`(=128000) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)
[09:24:12] stage1 blocks: 3
Both `max_new_tokens` (=1600) and `max_length`(=128000) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)
[09:24:16] stage2 components
Both `max_new_tokens` (=1600) and `max_length`(=128000) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)
[09:24:18] stage3 connections: 10
[09:24:18] verify round 1 issues: ["6 unconnected component(s) ['c4', 'c2', 'c9', 'c10', 'c3', 'c1']: wire each into the flow", 'under-connected: 10 connections for 12 components (expect >= 11)', "duplicate service(s) ['SAP HANA Cloud']: wire the existing one, do NOT add duplicate services"]
Both `max_new_tokens` (=1600) and `max_length`(=128000) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)
[09:24:26] verify round 2 issues: ["6 unconnected component(s) ['c4', 'c2', 'c9', 'c10', 'c3', 'c1']: wire each into the flow", 'under-connected: 10 connections for 12 components (expect >= 11)', "duplicate service(s) ['SAP HANA Cloud']: wire the existing one, do NOT add duplicate services"]
Both `max_new_tokens` (=1600) and `max_length`(=128000) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)
[09:24:34] final issues: ["6 unconnected component(s) ['c4', 'c2', 'c9', 'c10', 'c3', 'c1']: wire each into the flow", 'under-connected: 10 connections for 12 components (expect >= 11)', "duplicate service(s) ['SAP HANA Cloud']: wire the existing one, do NOT add duplicate services", 'Cloud Connector present but no SAP Connectivity service (incomplete on-prem tunnel).']
[09:24:34] EVAL {'arch': 'AI document agent (head-to-head)', 'ok': True, 'blocks': 6, 'components': 12, 'connections': 10, 'verify_rounds': 2, 'remaining_issues': ["6 unconnected component(s) ['c4', 'c2', 'c9', 'c10', 'c3', 'c1']: wire each into the flow", 'under-connected: 10 connections for 12 components (expect >= 11)', "duplicate service(s) ['SAP HANA Cloud']: wire the existing one, do NOT add duplicate services", 'Cloud Connector present but no SAP Connectivity service (incomplete on-prem tunnel).'], 'info': '19 nodes, 10 edges'}
Both `max_new_tokens` (=1600) and `max_length`(=128000) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)
[09:24:35] stage1 blocks: 2
Both `max_new_tokens` (=1600) and `max_length`(=128000) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)
[09:24:37] stage2 components
Both `max_new_tokens` (=1600) and `max_length`(=128000) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)
[09:24:39] stage3 connections: 8
[09:24:39] verify round 1 issues: ["duplicate component id(s) ['c0', 'c1', 'c2', 'c3', 'c4', 'c5', 'c6', 'c7', 'c8']: each component must appear once", "duplicate service(s) ['SAP Application Logan service', 'SAP Build Work Zone, standard', 'SAP Cloud Identity Services', 'SAP Connectivity service', 'SAP Destination service', 'SAP Document Management hub', 'SAP Private Link service', 'SAP Task Center']: wire the existing one, do NOT add duplicate services"]
Both `max_new_tokens` (=1600) and `max_length`(=128000) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)
[09:24:48] verify round 2 issues: ["duplicate component id(s) ['c0', 'c1', 'c2', 'c3', 'c4', 'c5', 'c6', 'c7', 'c8']: each component must appear once", "duplicate service(s) ['SAP Application Logan service', 'SAP Build Work Zone, standard', 'SAP Cloud Identity Services', 'SAP Connectivity service', 'SAP Destination service', 'SAP Document Management hub', 'SAP Private Link service', 'SAP Task Center']: wire the existing one, do NOT add duplicate services"]
Both `max_new_tokens` (=1600) and `max_length`(=128000) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)
[09:24:57] final issues: ["duplicate component id(s) ['c0', 'c1', 'c2', 'c3', 'c4', 'c5', 'c6', 'c7', 'c8']: each component must appear once", "duplicate service(s) ['SAP Application Logan service', 'SAP Build Work Zone, standard', 'SAP Cloud Identity Services', 'SAP Connectivity service', 'SAP Destination service', 'SAP Document Management hub', 'SAP Private Link service', 'SAP Task Center']: wire the existing one, do NOT add duplicate services"]
[09:24:57] EVAL {'arch': 'Task Center (known reference)', 'ok': True, 'blocks': 2, 'components': 18, 'connections': 8, 'verify_rounds': 2, 'remaining_issues': ["duplicate component id(s) ['c0', 'c1', 'c2', 'c3', 'c4', 'c5', 'c6', 'c7', 'c8']: each component must appear once", "duplicate service(s) ['SAP Application Logan service', 'SAP Build Work Zone, standard', 'SAP Cloud Identity Services', 'SAP Connectivity service', 'SAP Destination service', 'SAP Document Management hub', 'SAP Private Link service', 'SAP Task Center']: wire the existing one, do NOT add duplicate services"], 'info': '21 nodes, 8 edges'}
[09:24:57] QUALITY 5/6
[09:24:57] merging + pushing smjain/sap-archgen-lfm2-230M
Unsloth: Restored added_tokens_decoder metadata in merged16/tokenizer_config.json.
Found HuggingFace hub cache directory: /root/.cache/huggingface/hub
Checking cache directory for required files...
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Checking cache directory for required files...
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Unsloth: Restored added_tokens_decoder metadata in smjain/sap-archgen-lfm2-230M/tokenizer_config.json.
Unsloth: Merge process complete. Saved to `/work/merged16`
Found HuggingFace hub cache directory: /root/.cache/huggingface/hub
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Unsloth: Merge process complete. Saved to `/work/smjain/sap-archgen-lfm2-230M`
[09:25:36] GGUF via unsloth save_pretrained_gguf q4_0
Unsloth: Restored added_tokens_decoder metadata in gguf_out/tokenizer_config.json.
Unsloth: Merging model weights to 16-bit format...
Found HuggingFace hub cache directory: /root/.cache/huggingface/hub
Checking cache directory for required files...
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Successfully copied all 1 files from cache to `gguf_out`
Checking cache directory for required files...
Cache check failed: tokenizer.model not found in local cache.
Not all required files found in cache. Will proceed with downloading.
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Unsloth: Merge process complete. Saved to `/work/gguf_out`
Unsloth: Converting to GGUF format...
==((====))== Unsloth: Conversion from HF to GGUF information
 \\ /| [0] Installing llama.cpp might take 3 minutes.
O^O/ \_/ \ [1] Converting HF to GGUF bf16 might take 3 minutes.
\ / [2] Converting GGUF bf16 to ['q4_0'] might take 10 minutes each.
 "-____-" In total, you will have to wait at least 16 minutes.
Unsloth: Installing llama.cpp. This might take 3 minutes...
Unsloth: Installing prebuilt llama.cpp b9789-mix-1f1aaa4 (app-b9789-mix-1f1aaa4-linux-x64-cpu.tar.gz) - skipping compilation.
Unsloth: Preparing converter script...
Unsloth: [1] Converting model into bf16 GGUF format.
This might take 3 minutes...
Unsloth: Initial conversion completed! Files: ['gguf_out_gguf/LFM2.5-230M.BF16.gguf']
Unsloth: [2] Converting GGUF bf16 into q4_0. This might take 10 minutes...
Unsloth: Model files cleanup...
Unsloth: All GGUF conversions completed successfully!
Generated files: ['gguf_out_gguf/LFM2.5-230M.Q4_0.gguf']
Unsloth: No Ollama template mapping found for model 'unsloth/LFM2.5-230M'. Skipping Ollama Modelfile
Unsloth: example usage for text only LLMs: /root/.unsloth/llama.cpp/llama-cli --model gguf_out_gguf/LFM2.5-230M.Q4_0.gguf -p "why is the sky blue?"
[09:25:59] GGUF via llama.cpp convert_hf_to_gguf + quantize
Cloning into 'llama.cpp'...
ERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.
torchvision 0.25.0 requires torch==2.10.0, but you have torch 2.11.0+cpu which is incompatible.
unsloth 2026.6.9 requires torch<2.11.0,>=2.4.0, but you have torch 2.11.0+cpu which is incompatible.
torchaudio 2.4.1+cu124 requires torch==2.4.1, but you have torch 2.11.0+cpu which is incompatible.
WARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager, possibly rendering your system unusable.It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv. Use the --root-user-action option if you know what you are doing and want to suppress this warning.
[notice] A new release of pip is available: 24.2 -> 26.1.2
[notice] To update, run: python -m pip install --upgrade pip
[09:26:57] llama.cpp gguf failed FileNotFoundError(2, 'No such file or directory')
[09:26:57] GGUF EXPORT FAILED — merged16 is on smjain/sap-archgen-lfm2-230M ; convert locally
[09:26:57] ALL DONE 5 / 6