Instructions to use hf-internal-testing/tiny-random-GPTNeoXForTokenClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-GPTNeoXForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hf-internal-testing/tiny-random-GPTNeoXForTokenClassification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-GPTNeoXForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-internal-testing/tiny-random-GPTNeoXForTokenClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from hf-internal-testing/tiny-random-GPTNeoXForTokenClassification: direct link, hf CLI and curl.
- Browser
- Download file 1.59 MB
-
https://huggingface.co/hf-internal-testing/tiny-random-GPTNeoXForTokenClassification/resolve/refs%2Fpr%2F19/model.safetensors
- Command line
-
hf download hf://hf-internal-testing/tiny-random-GPTNeoXForTokenClassification@refs/pr/19/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-internal-testing/tiny-random-GPTNeoXForTokenClassification/resolve/refs%2Fpr%2F19/model.safetensors
1.59 MB
- Xet hash:
- 6b808d28acfa1e5e56d7e3b4717682e605c95139213c4eafcd2efd7dc9f55908
- Size of remote file:
- 1.59 MB
- SHA256:
- d1c9f3103bc1547d705a127ac39f3537fd4e1eca37e6dedd3257f6ac5be274f7
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