Instructions to use hf-internal-testing/tiny-random-NezhaForTokenClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-NezhaForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hf-internal-testing/tiny-random-NezhaForTokenClassification")# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForTokenClassification model = AutoModelForTokenClassification.from_pretrained("hf-internal-testing/tiny-random-NezhaForTokenClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from hf-internal-testing/tiny-random-NezhaForTokenClassification: direct link, hf CLI and curl.
- Browser
- Download file 2.91 MB
-
https://huggingface.co/hf-internal-testing/tiny-random-NezhaForTokenClassification/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://hf-internal-testing/tiny-random-NezhaForTokenClassification@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-internal-testing/tiny-random-NezhaForTokenClassification/resolve/refs%2Fpr%2F1/model.safetensors
2.91 MB
- Xet hash:
- d557ba648d404c98608ff74323e68cc245593c43d8f2cd77c3760a331695bba8
- Size of remote file:
- 2.91 MB
- SHA256:
- 9690c53617c0d5740334a92ab704dadd44f0415793d3c59559905e7a69e63f78
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