Instructions to use akhauriyash/DeepSeek-R1-Distill-Llama-8B-Butler with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use akhauriyash/DeepSeek-R1-Distill-Llama-8B-Butler with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="akhauriyash/DeepSeek-R1-Distill-Llama-8B-Butler", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("akhauriyash/DeepSeek-R1-Distill-Llama-8B-Butler", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
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The collection of TokenButler models can be found [here](https://huggingface.co/collections/akhauriyash/tokenbutler-67cf181b5762d0d60e5f312b). To run the `DeepSeek-R1-Distill-Llama-8B` model, follow:
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The collection of TokenButler models can be found [here](https://huggingface.co/collections/akhauriyash/tokenbutler-67cf181b5762d0d60e5f312b). To run the `DeepSeek-R1-Distill-Llama-8B` model, follow:
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