Commit From AutoTrain
Browse files- .gitattributes +3 -0
- README.md +49 -0
- config.json +45 -0
- pytorch_model.bin +3 -0
- special_tokens_map.json +7 -0
- tokenizer.json +3 -0
- tokenizer_config.json +14 -0
- vocab.txt +0 -0
.gitattributes
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*.zst filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.bin.* filter=lfs diff=lfs merge=lfs -text
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*.tar.gz filter=lfs diff=lfs merge=lfs -text
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tokenizer.json filter=lfs diff=lfs merge=lfs -text
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README.md
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---
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tags:
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- autotrain
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- token-classification
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language:
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- en
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widget:
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- text: "I love AutoTrain 🤗"
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datasets:
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- ankleBowl/autotrain-data-lucy-light-control
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co2_eq_emissions:
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emissions: 0.5335980780308736
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---
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# Model Trained Using AutoTrain
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- Problem type: Entity Extraction
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- Model ID: 3122788375
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- CO2 Emissions (in grams): 0.5336
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## Validation Metrics
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- Loss: 0.003
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- Accuracy: 1.000
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- Precision: 1.000
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- Recall: 1.000
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- F1: 1.000
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## Usage
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You can use cURL to access this model:
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```
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$ curl -X POST -H "Authorization: Bearer YOUR_API_KEY" -H "Content-Type: application/json" -d '{"inputs": "I love AutoTrain"}' https://api-inference.huggingface.co/models/ankleBowl/autotrain-lucy-light-control-3122788375
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```
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Or Python API:
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```
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from transformers import AutoModelForTokenClassification, AutoTokenizer
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model = AutoModelForTokenClassification.from_pretrained("ankleBowl/autotrain-lucy-light-control-3122788375", use_auth_token=True)
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tokenizer = AutoTokenizer.from_pretrained("ankleBowl/autotrain-lucy-light-control-3122788375", use_auth_token=True)
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inputs = tokenizer("I love AutoTrain", return_tensors="pt")
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outputs = model(**inputs)
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```
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config.json
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{
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"_name_or_path": "AutoTrain",
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"_num_labels": 7,
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"activation": "gelu",
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"architectures": [
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"DistilBertForTokenClassification"
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],
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"attention_dropout": 0.1,
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"dim": 768,
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"dropout": 0.1,
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"hidden_dim": 3072,
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"id2label": {
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"0": "BRI",
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"1": "COL",
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"2": "DIM",
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"3": "EMP",
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"4": "OFF",
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"5": "ONN",
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"6": "PER"
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},
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"initializer_range": 0.02,
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"label2id": {
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"BRI": 0,
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"COL": 1,
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"DIM": 2,
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"EMP": 3,
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"OFF": 4,
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"ONN": 5,
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"PER": 6
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},
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"max_length": 64,
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"max_position_embeddings": 512,
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"model_type": "distilbert",
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"n_heads": 12,
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"n_layers": 6,
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"pad_token_id": 0,
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"padding": "max_length",
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"qa_dropout": 0.1,
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"seq_classif_dropout": 0.2,
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"sinusoidal_pos_embds": false,
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"tie_weights_": true,
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"torch_dtype": "float32",
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"transformers_version": "4.25.1",
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"vocab_size": 30522
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}
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:3e9786d6a2e633896037b23c9f6e91984a4f56ce744b65ef79e9a23f2dd716ce
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size 265507877
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special_tokens_map.json
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{
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"cls_token": "[CLS]",
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"mask_token": "[MASK]",
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"pad_token": "[PAD]",
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"sep_token": "[SEP]",
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"unk_token": "[UNK]"
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}
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tokenizer.json
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version https://git-lfs.github.com/spec/v1
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oid sha256:41b9d12a4c559e4098f30173bc0f76d092c43d7b1f873e7027da45a256f30f87
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size 711659
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tokenizer_config.json
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{
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"cls_token": "[CLS]",
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"do_lower_case": true,
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"mask_token": "[MASK]",
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"model_max_length": 512,
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"name_or_path": "AutoTrain",
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"pad_token": "[PAD]",
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"sep_token": "[SEP]",
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"special_tokens_map_file": null,
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"strip_accents": null,
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"tokenize_chinese_chars": true,
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"tokenizer_class": "DistilBertTokenizer",
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"unk_token": "[UNK]"
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}
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vocab.txt
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