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Commit From AutoTrain

Browse files
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README.md ADDED
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+ ---
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+ tags:
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+ - autotrain
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+ - text-classification
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+ language:
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+ - unk
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+ widget:
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+ - text: "I love AutoTrain 🤗"
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+ datasets:
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+ - AyoubChLin/autotrain-data-delberta-large
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+ co2_eq_emissions:
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+ emissions: 4.083685268664441
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+ ---
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+
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+ # Model Trained Using AutoTrain
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+
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+ - Problem type: Multi-class Classification
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+ - Model ID: 48938118433
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+ - CO2 Emissions (in grams): 4.0837
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+
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+ ## Validation Metrics
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+
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+ - Loss: 0.130
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+ - Accuracy: 0.980
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+ - Macro F1: 0.980
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+ - Micro F1: 0.980
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+ - Weighted F1: 0.980
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+ - Macro Precision: 0.980
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+ - Micro Precision: 0.980
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+ - Weighted Precision: 0.980
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+ - Macro Recall: 0.980
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+ - Micro Recall: 0.980
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+ - Weighted Recall: 0.980
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+
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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 AutoTrain"}' https://api-inference.huggingface.co/models/AyoubChLin/autotrain-delberta-large-48938118433
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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("AyoubChLin/autotrain-delberta-large-48938118433", use_auth_token=True)
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+
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+ tokenizer = AutoTokenizer.from_pretrained("AyoubChLin/autotrain-delberta-large-48938118433", use_auth_token=True)
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+
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+ inputs = tokenizer("I love AutoTrain", 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": "AutoTrain",
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+ ],
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+ "layer_norm_eps": 1e-07,
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+ "max_length": 512,
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+ "max_position_embeddings": 512,
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+ "max_relative_positions": -1,
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+ "model_type": "deberta-v2",
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+ "norm_rel_ebd": "layer_norm",
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+ "num_attention_heads": 16,
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+ "num_hidden_layers": 24,
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+ "pad_token_id": 0,
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+ "pooler_dropout": 0,
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+ "pooler_hidden_size": 1024,
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+ "pos_att_type": [
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+ "p2c",
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+ "c2p"
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+ "position_biased_input": false,
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