Commit From AutoNLP
Browse files- .gitattributes +2 -0
- README.md +44 -0
- config.json +36 -0
- pytorch_model.bin +3 -0
- sample_input.pkl +3 -0
- special_tokens_map.json +1 -0
- tokenizer.json +0 -0
- tokenizer_config.json +1 -0
- vocab.txt +0 -0
.gitattributes
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zstandard filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zstandard filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.tar.gz filter=lfs diff=lfs merge=lfs -text
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*.pkl filter=lfs diff=lfs merge=lfs -text
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README.md
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---
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tags: autonlp
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language: unk
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widget:
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- text: "I love AutoNLP 🤗"
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datasets:
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- Adi2K/autonlp-data-Priv-Consent
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---
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# Model Trained Using AutoNLP
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- Problem type: Binary Classification
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- Model ID: 12592372
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## Validation Metrics
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- Loss: 0.23033875226974487
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- Accuracy: 0.9138655462184874
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- Precision: 0.9087136929460581
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- Recall: 0.9201680672268907
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- AUC: 0.9690346726926065
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- F1: 0.9144050104384133
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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 AutoNLP"}' https://api-inference.huggingface.co/models/Adi2K/autonlp-Priv-Consent-12592372
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```
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Or Python API:
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```
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from transformers import AutoModelForSequenceClassification, AutoTokenizer
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model = AutoModelForSequenceClassification.from_pretrained("Adi2K/autonlp-Priv-Consent-12592372", use_auth_token=True)
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tokenizer = AutoTokenizer.from_pretrained("Adi2K/autonlp-Priv-Consent-12592372", use_auth_token=True)
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inputs = tokenizer("I love AutoNLP", 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": "AutoNLP",
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"_num_labels": 2,
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"architectures": [
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"BertForSequenceClassification"
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],
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"attention_probs_dropout_prob": 0.1,
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"gradient_checkpointing": false,
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.1,
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"hidden_size": 768,
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"id2label": {
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"0": "CON",
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"1": "NOT"
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},
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"label2id": {
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"CON": 0,
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"NOT": 1
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},
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"layer_norm_eps": 1e-12,
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"max_length": 256,
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"max_position_embeddings": 512,
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"model_type": "bert",
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"num_attention_heads": 12,
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"num_hidden_layers": 12,
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"pad_token_id": 0,
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"padding": "max_length",
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"position_embedding_type": "absolute",
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"problem_type": "single_label_classification",
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"transformers_version": "4.8.0",
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"type_vocab_size": 2,
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"use_cache": true,
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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 sha256:6384d75336913f1262dd77246ee177b9217b27591a30f13b292d9e59acc7cfdc
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size 438019245
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sample_input.pkl
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version https://git-lfs.github.com/spec/v1
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oid sha256:2ff6609aace6ac6ef7f1834260dc8a828ab1607933f7900a61f045e596097a88
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size 7462
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special_tokens_map.json
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{"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}
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tokenizer.json
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tokenizer_config.json
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{"do_lower_case": true, "unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]", "tokenize_chinese_chars": true, "strip_accents": null, "model_max_length": 512, "special_tokens_map_file": null, "name_or_path": "AutoNLP", "tokenizer_class": "BertTokenizer"}
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vocab.txt
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