Instructions to use toshi456/llava-jp-1.3b-v1.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use toshi456/llava-jp-1.3b-v1.0 with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "image-to-text" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("image-to-text", model="toshi456/llava-jp-1.3b-v1.0")# Load model directly from transformers import AutoProcessor, AutoModelForCausalLM processor = AutoProcessor.from_pretrained("toshi456/llava-jp-1.3b-v1.0") model = AutoModelForCausalLM.from_pretrained("toshi456/llava-jp-1.3b-v1.0", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a57c47e174aa3fc0fe1f1de12ee2186e0b318998252ad4d630b64f87c21c7203
- Size of remote file:
- 1.32 GB
- SHA256:
- e4e4033828bf76b5f3a44e704b9bfe1ffab54714ac601d72e4b3003200209bfc
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