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:
- a77fa64a9f8c6b75784d47201fd716e9c6720c7f8a8bba5baba4b3d543a8983d
- Size of remote file:
- 28.3 MB
- SHA256:
- afb38307e6972742217124ade6951388667f472824ef839fb9fea9aea4666589
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