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:
- 35e5bb37f7532ed5d1e8afe0cdd2387e0c2f52e34c09bb20943268933373fc5c
- Size of remote file:
- 33.1 MB
- SHA256:
- c90c67cc7a36bb5c3ebadbdebacf8705ab20d727ea5b03c3ed157470792ba703
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