Instructions to use hf-internal-testing/tiny-random-GPTNeoXForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-GPTNeoXForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-internal-testing/tiny-random-GPTNeoXForSequenceClassification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-GPTNeoXForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-internal-testing/tiny-random-GPTNeoXForSequenceClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from hf-internal-testing/tiny-random-GPTNeoXForSequenceClassification: direct link, hf CLI and curl.
- Browser
- Download file 1.6 MB
-
https://huggingface.co/hf-internal-testing/tiny-random-GPTNeoXForSequenceClassification/resolve/383f9205f1fa2d70c38833d008354b59e2dfd09b/pytorch_model.bin
- Command line
-
hf download hf://hf-internal-testing/tiny-random-GPTNeoXForSequenceClassification@383f9205f1fa2d70c38833d008354b59e2dfd09b/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/hf-internal-testing/tiny-random-GPTNeoXForSequenceClassification/resolve/383f9205f1fa2d70c38833d008354b59e2dfd09b/pytorch_model.bin
1.6 MB
- Xet hash:
- 1d017e408c2980f5963ff67c1a4275dc872a6c5b5cc7e023a275c3113ae8b62c
- Size of remote file:
- 1.6 MB
- SHA256:
- edd58bef7eefa7cfdd3b59ff1dea56d96fb22ce7a4394d9f987f40081502c2cd
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