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Commit From AutoTrain

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.gitattributes CHANGED
@@ -32,3 +32,6 @@ 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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  *.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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+ *.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
README.md ADDED
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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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+ - unk
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+ widget:
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+ - text: "I love AutoTrain 🤗"
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+ datasets:
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+ - tinyYhorm/autotrain-data-2-roberta-r
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+ co2_eq_emissions:
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+ emissions: 0.7754785356509495
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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: Entity Extraction
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+ - Model ID: 53890126861
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+ - CO2 Emissions (in grams): 0.7755
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+
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+ ## Validation Metrics
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+
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+ - Loss: 0.178
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+ - Accuracy: 0.958
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+ - Precision: 0.868
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+ - Recall: 0.877
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+ - F1: 0.873
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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/tinyYhorm/autotrain-2-roberta-r-53890126861
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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 AutoModelForTokenClassification, AutoTokenizer
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+
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+ model = AutoModelForTokenClassification.from_pretrained("tinyYhorm/autotrain-2-roberta-r-53890126861", use_auth_token=True)
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+
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+ tokenizer = AutoTokenizer.from_pretrained("tinyYhorm/autotrain-2-roberta-r-53890126861", 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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+ ```
config.json ADDED
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+ {
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+ "_name_or_path": "AutoTrain",
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+ "_num_labels": 21,
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+ "architectures": [
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+ "BertForTokenClassification"
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+ ],
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+ "directionality": "bidi",
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+ "eos_token_id": 2,
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+ "hidden_act": "gelu",
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+ "hidden_size": 768,
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+ "id2label": {
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+ "0": "B-Case",
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+ "use_cache": true,
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+ }
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