Instructions to use hf-internal-testing/tiny-random-XmodForTokenClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-XmodForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hf-internal-testing/tiny-random-XmodForTokenClassification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-XmodForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-internal-testing/tiny-random-XmodForTokenClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from hf-internal-testing/tiny-random-XmodForTokenClassification: direct link, hf CLI and curl.
- Browser
- Download file 32.2 MB
-
https://huggingface.co/hf-internal-testing/tiny-random-XmodForTokenClassification/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://hf-internal-testing/tiny-random-XmodForTokenClassification@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-internal-testing/tiny-random-XmodForTokenClassification/resolve/refs%2Fpr%2F1/model.safetensors
32.2 MB
- Xet hash:
- e979542b866c06fc4f39a500de818bb7da2d1093d87624894db87719b6c7a8ac
- Size of remote file:
- 32.2 MB
- SHA256:
- bc77dad34e9318ec3ece577673dfcd7132ea81afca943c6e97d79b19678bdc14
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