Instructions to use hf-internal-testing/tiny-llama with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-llama with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-llama")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-llama") model = AutoModel.from_pretrained("hf-internal-testing/tiny-llama") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7aa69939689114ca378388b5c6be563e567886683e721dbdadb28724e59ac6ed
- Size of remote file:
- 14.9 kB
- SHA256:
- 07d98719bb95a2640bbf46912debaefa512967f6625ae9a324f4101ec458a333
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