abhishek HF staff commited on
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5229617
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Commit From AutoNLP

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.gitattributes CHANGED
@@ -25,3 +25,5 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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  *.zip filter=lfs diff=lfs merge=lfs -text
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+ *.pkl filter=lfs diff=lfs merge=lfs -text
README.md ADDED
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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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+ - pediberto/autonlp-data-testing
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+ co2_eq_emissions: 12.994518654810642
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+ ---
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+
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+ # Model Trained Using AutoNLP
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+
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+ - Problem type: Binary Classification
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+ - Model ID: 504313966
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+ - CO2 Emissions (in grams): 12.994518654810642
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+
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+ ## Validation Metrics
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+
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+ - Loss: 0.19673296809196472
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+ - Accuracy: 0.9398032027783138
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+ - Precision: 0.9133115705476967
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+ - Recall: 0.9718255499807025
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+ - AUC: 0.985316873222122
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+ - F1: 0.9416604338070308
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+
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+ ## Usage
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+
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+ You can use cURL to access this model:
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+
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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/pediberto/autonlp-testing-504313966
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+ ```
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+
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+ Or Python API:
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+
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+ ```
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+ from transformers import AutoModelForSequenceClassification, AutoTokenizer
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+
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+ model = AutoModelForSequenceClassification.from_pretrained("pediberto/autonlp-testing-504313966", use_auth_token=True)
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+
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+ tokenizer = AutoTokenizer.from_pretrained("pediberto/autonlp-testing-504313966", use_auth_token=True)
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+
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+ inputs = tokenizer("I love AutoNLP", return_tensors="pt")
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+
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+ outputs = model(**inputs)
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+ ```
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+ "_name_or_path": "AutoNLP",
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+ "architectures": [
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+ "hidden_act": "gelu",
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+ "id2label": {
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+ },
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+ "layer_norm_eps": 1e-05,
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+ "max_length": 128,
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+ "max_position_embeddings": 130,
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+ "model_type": "roberta",
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+ "num_attention_heads": 12,
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+ "num_hidden_layers": 12,
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+ "pad_token_id": 1,
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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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+ "tokenizer_class": "BertweetTokenizer",
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.15.0",
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+ "type_vocab_size": 1,
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+ "use_cache": true,
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+ "vocab_size": 64001
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+ }
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