Commit From AutoTrain

.gitattributes

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 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+*.bin.* filter=lfs diff=lfs merge=lfs -text
+*.tar.gz filter=lfs diff=lfs merge=lfs -text
+tokenizer.json filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,56 @@
+---
+tags:
+- autotrain
+- text-classification
+language:
+- en
+widget:
+- text: "I love AutoTrain 🤗"
+datasets:
+- vkheman/autotrain-data-multic
+co2_eq_emissions:
+  emissions: 1.3867154772046042
+---
+
+# Model Trained Using AutoTrain
+
+- Problem type: Multi-class Classification
+- Model ID: 42139108182
+- CO2 Emissions (in grams): 1.3867
+
+## Validation Metrics
+
+- Loss: 0.758
+- Accuracy: 0.836
+- Macro F1: 0.835
+- Micro F1: 0.836
+- Weighted F1: 0.836
+- Macro Precision: 0.839
+- Micro Precision: 0.836
+- Weighted Precision: 0.840
+- Macro Recall: 0.836
+- Micro Recall: 0.836
+- Weighted Recall: 0.836
+
+
+## Usage
+
+You can use cURL to access this model:
+
+```
+$ 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/vkheman/autotrain-multic-42139108182
+```
+
+Or Python API:
+
+```
+from transformers import AutoModelForSequenceClassification, AutoTokenizer
+
+model = AutoModelForSequenceClassification.from_pretrained("vkheman/autotrain-multic-42139108182", use_auth_token=True)
+
+tokenizer = AutoTokenizer.from_pretrained("vkheman/autotrain-multic-42139108182", use_auth_token=True)
+
+inputs = tokenizer("I love AutoTrain", return_tensors="pt")
+
+outputs = model(**inputs)
+```

config.json

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+{
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+  "padding": "max_length",
+  "position_embedding_type": "absolute",
+  "problem_type": "single_label_classification",
+  "torch_dtype": "float32",
+  "transformers_version": "4.25.1",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30522
+}

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special_tokens_map.json

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tokenizer.json

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tokenizer_config.json

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+}