Instructions to use BUAADreamer/Chinese-LLaVA-Med-7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BUAADreamer/Chinese-LLaVA-Med-7B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("visual-question-answering", model="BUAADreamer/Chinese-LLaVA-Med-7B")# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("BUAADreamer/Chinese-LLaVA-Med-7B") model = AutoModelForMultimodalLM.from_pretrained("BUAADreamer/Chinese-LLaVA-Med-7B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2efb80bbdc88936b0a098d49f550efe01d6637da546f6a86a7832a2dcc25a178
- Size of remote file:
- 1.99 GB
- SHA256:
- 876568578502e0514c6874d2c76a9d3d5f98ac8b59fec4233e59febb17eb98e7
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