Instructions to use YsnHdn/Model_PFE with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use YsnHdn/Model_PFE with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="YsnHdn/Model_PFE")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("YsnHdn/Model_PFE") model = AutoModelForSequenceClassification.from_pretrained("YsnHdn/Model_PFE", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download label_encoder.pkl from YsnHdn/Model_PFE: direct link, hf CLI and curl.
- Browser
- Download file 227 Bytes
-
https://huggingface.co/YsnHdn/Model_PFE/resolve/main/label_encoder.pkl
- Command line
-
hf download hf://YsnHdn/Model_PFE/label_encoder.pkl
-
curl -L -o label_encoder.pkl https://huggingface.co/YsnHdn/Model_PFE/resolve/main/label_encoder.pkl
227 Bytes
- Xet hash:
- 93aa4f05108a82f47bc9263e1d680ad3dc498f55dfb70a97104f7aafeb4f2bb3
- Size of remote file:
- 227 Bytes
- SHA256:
- 6f2140f9641061e34cfa413940d8b885b3016267e372ed6b7878908a47ab4759
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