Instructions to use clam004/distilbert-coherent-v5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use clam004/distilbert-coherent-v5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="clam004/distilbert-coherent-v5")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("clam004/distilbert-coherent-v5") model = AutoModelForSequenceClassification.from_pretrained("clam004/distilbert-coherent-v5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from clam004/distilbert-coherent-v5: direct link, hf CLI and curl.
- Browser
- Download file 268 MB
-
https://huggingface.co/clam004/distilbert-coherent-v5/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://clam004/distilbert-coherent-v5@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/clam004/distilbert-coherent-v5/resolve/refs%2Fpr%2F1/pytorch_model.bin
268 MB
- Xet hash:
- e4f97fcd640036819b4c7e1ed9bb181cbd05d3ea35b916e0aa3d5b1a427d3294
- Size of remote file:
- 268 MB
- SHA256:
- 2fa07bf4a1a585e4700e6f038ebb5e3c498bf9e584162713914b0266196a8724
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