Instructions to use shimbaaa/mat-classifier-0.5b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shimbaaa/mat-classifier-0.5b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="shimbaaa/mat-classifier-0.5b")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("shimbaaa/mat-classifier-0.5b", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from shimbaaa/mat-classifier-0.5b: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/shimbaaa/mat-classifier-0.5b/resolve/main/tokenizer.json
- Command line
-
hf download hf://shimbaaa/mat-classifier-0.5b/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/shimbaaa/mat-classifier-0.5b/resolve/main/tokenizer.json
11.4 MB
- Xet hash:
- 81a0f539b45dc2b953d2293dada19064ba7420d99f7007bbb2305496ca8e072c
- Size of remote file:
- 11.4 MB
- SHA256:
- 81457677bc3d07e5e184fc721d57094eb3c0bae647660981ec33364acf5479c9
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