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Commit From AutoTrain

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.gitattributes CHANGED
@@ -33,3 +33,6 @@ saved_model/**/* 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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+ - sxandie/autotrain-data-air-sea-services-28092023
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+ co2_eq_emissions:
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+ emissions: 0.8518554225909252
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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: 91915144626
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+ - CO2 Emissions (in grams): 0.8519
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+
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+ ## Validation Metrics
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+
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+ - Loss: 0.921
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+ - Accuracy: 0.759
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+ - Precision: 0.159
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+ - Recall: 0.098
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+ - F1: 0.122
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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/sxandie/autotrain-air-sea-services-28092023-91915144626
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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("sxandie/autotrain-air-sea-services-28092023-91915144626", use_auth_token=True)
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+
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+ tokenizer = AutoTokenizer.from_pretrained("sxandie/autotrain-air-sea-services-28092023-91915144626", 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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+ "hidden_act": "gelu",
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+ "hidden_size": 768,
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+ "id2label": {
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+ "0": "O",
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+ "1": "commodity",
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+ "2": "company",
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+ "3": "delivery_cap",
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+ "4": "delivery_location",
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+ "5": "delivery_port",
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+ "6": "delivery_state",
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+ "7": "incoterms",
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+ "8": "measures",
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+ "9": "package_type",
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+ "13": "quantity",
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+ "14": "stackable",
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+ "use_cache": true,
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