Instructions to use trl-internal-testing/tiny-GPTNeoXForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use trl-internal-testing/tiny-GPTNeoXForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="trl-internal-testing/tiny-GPTNeoXForSequenceClassification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("trl-internal-testing/tiny-GPTNeoXForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("trl-internal-testing/tiny-GPTNeoXForSequenceClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from trl-internal-testing/tiny-GPTNeoXForSequenceClassification: direct link, hf CLI and curl.
- Browser
- Download file 1.62 MB
-
https://huggingface.co/trl-internal-testing/tiny-GPTNeoXForSequenceClassification/resolve/main/model.safetensors
- Command line
-
hf download hf://trl-internal-testing/tiny-GPTNeoXForSequenceClassification/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/trl-internal-testing/tiny-GPTNeoXForSequenceClassification/resolve/main/model.safetensors
1.62 MB
- Xet hash:
- eb4e90301ad8a506f7655239f7e06ae5b7da65ec0651c07a5f52fbd8c272194e
- Size of remote file:
- 1.62 MB
- SHA256:
- 48bd64a338a57c4ab9ba751c4a49c7e8a5f63913ae60f063ecf52c2d18fc4ce9
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