Instructions to use am-azadi/best-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use am-azadi/best-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="am-azadi/best-model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("am-azadi/best-model") model = AutoModelForSequenceClassification.from_pretrained("am-azadi/best-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from am-azadi/best-model: direct link, hf CLI and curl.
- Browser
- Download file 17.1 MB
-
https://huggingface.co/am-azadi/best-model/resolve/main/tokenizer.json
- Command line
-
hf download hf://am-azadi/best-model/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/am-azadi/best-model/resolve/main/tokenizer.json
17.1 MB
- Xet hash:
- 0abd02c8ae3c446b4b196b4041ef6b8dc3dce7d172091fa5ca5ce17b4eb7d627
- Size of remote file:
- 17.1 MB
- SHA256:
- f59925fcb90c92b894cb93e51bb9b4a6105c5c249fe54ce1c704420ac39b81af
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