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:
- 93ae9e9eaf5ed34673cb0f9a40bbd2e9d1d9e60b93e381c2e234e9ac95d65880
- Size of remote file:
- 4.92 MB
- SHA256:
- c49dc7e82c10227af764e518924cf2f9d50c00462750d184fa74697bba65eef8
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