Instructions to use TransQuest/monotransquest-hter-en_zh-wiki with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TransQuest/monotransquest-hter-en_zh-wiki with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="TransQuest/monotransquest-hter-en_zh-wiki")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("TransQuest/monotransquest-hter-en_zh-wiki") model = AutoModelForSequenceClassification.from_pretrained("TransQuest/monotransquest-hter-en_zh-wiki") - Notebooks
- Google Colab
- Kaggle
Commit ·
49fef6e
1
Parent(s): 95e2fd2
from Google Colab
Browse files- config.json +53 -0
- eval_results.txt +4 -0
- pytorch_model.bin +3 -0
- sentencepiece.bpe.model +3 -0
- special_tokens_map.json +1 -0
- tokenizer_config.json +1 -0
config.json
ADDED
|
@@ -0,0 +1,53 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"_num_labels": 1,
|
| 3 |
+
"architectures": [
|
| 4 |
+
"XLMRobertaForSequenceClassification"
|
| 5 |
+
],
|
| 6 |
+
"attention_probs_dropout_prob": 0.1,
|
| 7 |
+
"bad_words_ids": null,
|
| 8 |
+
"bos_token_id": 0,
|
| 9 |
+
"decoder_start_token_id": null,
|
| 10 |
+
"do_sample": false,
|
| 11 |
+
"early_stopping": false,
|
| 12 |
+
"eos_token_id": 2,
|
| 13 |
+
"finetuning_task": null,
|
| 14 |
+
"hidden_act": "gelu",
|
| 15 |
+
"hidden_dropout_prob": 0.1,
|
| 16 |
+
"hidden_size": 1024,
|
| 17 |
+
"id2label": {
|
| 18 |
+
"0": "LABEL_0"
|
| 19 |
+
},
|
| 20 |
+
"initializer_range": 0.02,
|
| 21 |
+
"intermediate_size": 4096,
|
| 22 |
+
"is_decoder": false,
|
| 23 |
+
"is_encoder_decoder": false,
|
| 24 |
+
"label2id": {
|
| 25 |
+
"LABEL_0": 0
|
| 26 |
+
},
|
| 27 |
+
"layer_norm_eps": 1e-05,
|
| 28 |
+
"length_penalty": 1.0,
|
| 29 |
+
"max_length": 20,
|
| 30 |
+
"max_position_embeddings": 514,
|
| 31 |
+
"min_length": 0,
|
| 32 |
+
"model_type": "xlm-roberta",
|
| 33 |
+
"no_repeat_ngram_size": 0,
|
| 34 |
+
"num_attention_heads": 16,
|
| 35 |
+
"num_beams": 1,
|
| 36 |
+
"num_hidden_layers": 24,
|
| 37 |
+
"num_return_sequences": 1,
|
| 38 |
+
"output_attentions": false,
|
| 39 |
+
"output_hidden_states": false,
|
| 40 |
+
"output_past": true,
|
| 41 |
+
"pad_token_id": 1,
|
| 42 |
+
"prefix": null,
|
| 43 |
+
"pruned_heads": {},
|
| 44 |
+
"repetition_penalty": 1.0,
|
| 45 |
+
"task_specific_params": null,
|
| 46 |
+
"temperature": 1.0,
|
| 47 |
+
"top_k": 50,
|
| 48 |
+
"top_p": 1.0,
|
| 49 |
+
"torchscript": false,
|
| 50 |
+
"type_vocab_size": 1,
|
| 51 |
+
"use_bfloat16": false,
|
| 52 |
+
"vocab_size": 250002
|
| 53 |
+
}
|
eval_results.txt
ADDED
|
@@ -0,0 +1,4 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
eval_loss = 0.02853513140231371
|
| 2 |
+
mae = 0.1350894
|
| 3 |
+
pearson_corr = 0.5575486159307658
|
| 4 |
+
spearman_corr = 0.5595193583474529
|
pytorch_model.bin
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:53b807fe1889764bae991263dc2e3866b4892b3725f0a8a252bb4c8b73531fa6
|
| 3 |
+
size 2243863388
|
sentencepiece.bpe.model
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:cfc8146abe2a0488e9e2a0c56de7952f7c11ab059eca145a0a727afce0db2865
|
| 3 |
+
size 5069051
|
special_tokens_map.json
ADDED
|
@@ -0,0 +1 @@
|
|
|
|
|
|
|
| 1 |
+
{"bos_token": "<s>", "eos_token": "</s>", "unk_token": "<unk>", "sep_token": "</s>", "pad_token": "<pad>", "cls_token": "<s>", "mask_token": "<mask>"}
|
tokenizer_config.json
ADDED
|
@@ -0,0 +1 @@
|
|
|
|
|
|
|
| 1 |
+
{"do_lower_case": false, "max_len": 512}
|