ipatate
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update doc
Browse files- README.md +9 -4
- config.json +2 -2
README.md
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## Usage
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```python
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from transformers import AutoTokenizer, AutoModelForSequenceClassification
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model_name = "Goodmotion/spam-mail-classifier"
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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model = AutoModelForSequenceClassification.from_pretrained(
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text = "Félicitations ! Vous avez gagné un iPhone."
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inputs = tokenizer(text, return_tensors="pt")
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outputs = model(**inputs)
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print(outputs.logits)
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```
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model_name = "Goodmotion/spam-mail-classifier"
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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model = AutoModelForSequenceClassification.from_pretrained(model_name)
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texts = [
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'Join us for a webinar on AI innovations',
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## Usage
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This model is fine-tuned from `microsoft/Multilingual-MiniLM-L12-H384` to classify email subjects as SPAM or NOSPAM.
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### Loading the model
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To load this model, ensure you specify `from_safetensors=True`:
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```python
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from transformers import AutoTokenizer, AutoModelForSequenceClassification
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model_name = "Goodmotion/spam-mail-classifier"
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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model = AutoModelForSequenceClassification.from_pretrained(
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model_name, from_safetensors=True
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)
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text = "Félicitations ! Vous avez gagné un iPhone."
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inputs = tokenizer(text, return_tensors="pt")
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outputs = model(**inputs)
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print(outputs.logits)
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```
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model_name = "Goodmotion/spam-mail-classifier"
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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model = AutoModelForSequenceClassification.from_pretrained(model_name,from_safetensors=True)
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texts = [
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'Join us for a webinar on AI innovations',
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config.json
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size
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version https://git-lfs.github.com/spec/v1
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oid sha256:9dad0e77cb2fdbd8f66acdc9e26e06651be2490dfcdf6e428bb09f1aaf5df7cd
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size 796
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