Instructions to use hf-internal-testing/tiny-random-XGLMModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-XGLMModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-XGLMModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-XGLMModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-XGLMModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 933d83b625b719784e33fcd562e54cf4610c0a4aab263423f3114d768fe52e39
- Size of remote file:
- 33 MB
- SHA256:
- 6537dc4958d73b88cd5ee1b2642c536cd1c3fc24fd74431a84c1f80ca6a21d3e
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