Instructions to use voidful/Llama-Typhoon-8B-R1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use voidful/Llama-Typhoon-8B-R1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="voidful/Llama-Typhoon-8B-R1", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("voidful/Llama-Typhoon-8B-R1", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- deb5582d6e30fb16b6fa4c62f5916d2b754f08d71dbd0363fec20fc10d738bec
- Size of remote file:
- 10.5 MB
- SHA256:
- 806ed9a6e543768a0e67535c59218095a191e6cfb85ca8b7e3e8b208458c74df
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