Instructions to use xtuner/llava-llama-3-8b-v1_1-pretrain with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use xtuner/llava-llama-3-8b-v1_1-pretrain with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("visual-question-answering", model="xtuner/llava-llama-3-8b-v1_1-pretrain")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("xtuner/llava-llama-3-8b-v1_1-pretrain", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8c5e44e4fd3729c84227e665ad52293fcce83d2595da8ff44c0a2488eb8c5c6b
- Size of remote file:
- 42.7 MB
- SHA256:
- 73eb1e9dcd3caef11442a257c6e5ce4b2aacbbcc694fc610d65633ba8ce9d0f0
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