system HF staff commited on
Commit
0711bcf
1 Parent(s): ec2bd8c

Commit From AutoTrain

Browse files
.gitattributes CHANGED
@@ -30,3 +30,5 @@ 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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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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+ - en
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+ widget:
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+ - text: "I love AutoTrain 🤗"
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+ datasets:
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+ - neuralspace/autotrain-data-ecomm1.8
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+ co2_eq_emissions:
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+ emissions: 0.034797737604122594
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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: 1360552485
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+ - CO2 Emissions (in grams): 0.0348
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+
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+ ## Validation Metrics
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+
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+ - Loss: 0.539
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+ - Accuracy: 0.914
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+ - Macro F1: 0.903
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+ - Micro F1: 0.914
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+ - Weighted F1: 0.907
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+ - Macro Precision: 0.927
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+ - Micro Precision: 0.914
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+ - Weighted Precision: 0.928
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+ - Macro Recall: 0.907
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+ - Micro Recall: 0.914
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+ - Weighted Recall: 0.914
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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/neuralspace/autotrain-ecomm1.8-1360552485
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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("neuralspace/autotrain-ecomm1.8-1360552485", use_auth_token=True)
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+
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+ tokenizer = AutoTokenizer.from_pretrained("neuralspace/autotrain-ecomm1.8-1360552485", 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": 188,
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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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+ "0": "Activate",
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+ "1": "Add",
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+ "2": "Adjust",
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+ "3": "Advertize",
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+ "4": "Allocate",
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+ "43": "Download",
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+ "44": "Draft",
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+ "45": "E-mail",
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+ "46": "Enter",
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+ "47": "Evaluate",
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+ "48": "Examine",
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