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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7c255b5d1098953c0d25f5ec64fc5f53d53cc4257009a0a1b4135b4115ed05d4
- Size of remote file:
- 33 MB
- SHA256:
- 2856fd460960c18949188cab37e9a9688063c889ee30717fa6c018bfc1ff9b5f
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