Commit From AutoTrain

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Files changed (8) hide show

.gitattributes +3 -0
README.md +56 -0
config.json +161 -0
pytorch_model.bin +3 -0
special_tokens_map.json +7 -0
tokenizer.json +3 -0
tokenizer_config.json +16 -0
vocab.txt +0 -0

.gitattributes CHANGED Viewed

@@ -32,3 +32,6 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text

 *.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 ADDED Viewed

	@@ -0,0 +1,56 @@

+---
+tags:
+- autotrain
+- text-classification
+language:
+- unk
+widget:
+- text: "I love AutoTrain 🤗"
+datasets:
+- IRI2070/autotrain-data-intacode-144510011402
+co2_eq_emissions:
+  emissions: 0.5929314842324308
+---
+# Model Trained Using AutoTrain
+- Problem type: Multi-class Classification
+- Model ID: 45720114293
+- CO2 Emissions (in grams): 0.5929
+## Validation Metrics
+- Loss: 0.811
+- Accuracy: 0.911
+- Macro F1: 0.735
+- Micro F1: 0.911
+- Weighted F1: 0.895
+- Macro Precision: 0.730
+- Micro Precision: 0.911
+- Weighted Precision: 0.882
+- Macro Recall: 0.742
+- Micro Recall: 0.911
+- Weighted Recall: 0.911
+## 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/IRI2070/autotrain-intacode-144510011402-45720114293
+```
+Or Python API:
+```
+from transformers import AutoModelForSequenceClassification, AutoTokenizer
+model = AutoModelForSequenceClassification.from_pretrained("IRI2070/autotrain-intacode-144510011402-45720114293", use_auth_token=True)
+tokenizer = AutoTokenizer.from_pretrained("IRI2070/autotrain-intacode-144510011402-45720114293", use_auth_token=True)
+inputs = tokenizer("I love AutoTrain", return_tensors="pt")
+outputs = model(**inputs)
+```

config.json ADDED Viewed

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vocab.txt ADDED Viewed

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