Instructions to use h1alexbel/github-samples-tclassifier-testing with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use h1alexbel/github-samples-tclassifier-testing with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="h1alexbel/github-samples-tclassifier-testing")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("h1alexbel/github-samples-tclassifier-testing") model = AutoModelForSequenceClassification.from_pretrained("h1alexbel/github-samples-tclassifier-testing", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from h1alexbel/github-samples-tclassifier-testing: direct link, hf CLI and curl.
- Browser
- Download file 268 MB
-
https://huggingface.co/h1alexbel/github-samples-tclassifier-testing/resolve/main/model.safetensors
- Command line
-
hf download hf://h1alexbel/github-samples-tclassifier-testing/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/h1alexbel/github-samples-tclassifier-testing/resolve/main/model.safetensors
268 MB
- Xet hash:
- c3835a41be301aa6a29b1a860d5668f8a0e44e8d59213a807ee40809642bd308
- Size of remote file:
- 268 MB
- SHA256:
- 7cdb36b7db0655f031879263267e448c1cb5b3fb8a005985232c337a133fd104
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