Instructions to use nllg/clf-canine-m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nllg/clf-canine-m with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="nllg/clf-canine-m")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("nllg/clf-canine-m") model = AutoModelForSequenceClassification.from_pretrained("nllg/clf-canine-m", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from nllg/clf-canine-m: direct link, hf CLI and curl.
- Browser
- Download file 529 MB
-
https://huggingface.co/nllg/clf-canine-m/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://nllg/clf-canine-m/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/nllg/clf-canine-m/resolve/main/pytorch_model.bin
529 MB
- Xet hash:
- 845533036a6c0c4bb7c843a4ac3f011d8f69d30c015ad38a4715ff787d022df4
- Size of remote file:
- 529 MB
- SHA256:
- ca2394e51b4ca39724bece986bd937e2a2ae3d8ad430ef265fdbba62aa76a328
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