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/17c4b845ee2e0bb780ca2dea2d59a3d9d5d3c651/pytorch_model.bin
- Command line
-
hf download hf://hf-internal-testing/tiny-random-GPTNeoXForSequenceClassification@17c4b845ee2e0bb780ca2dea2d59a3d9d5d3c651/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/hf-internal-testing/tiny-random-GPTNeoXForSequenceClassification/resolve/17c4b845ee2e0bb780ca2dea2d59a3d9d5d3c651/pytorch_model.bin
1.6 MB
- Xet hash:
- 3d4c3c44504e6e48c4fcecb6e5f704558c2ee40b8d8145900b78e3fb4d533557
- Size of remote file:
- 1.6 MB
- SHA256:
- 978a3f26741751043da3bbe01f9c9388613251cd8c355081749582caabfc4101
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