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:
- 71e4892c557ee2f47ebcafcecdbc33eb85a5250e3af981e669d1cfc109161d6c
- Size of remote file:
- 5 GB
- SHA256:
- 743d589796ee4b372d5f5bfb9bec4e30481a98e50fa9e8c5929f119216501e7b
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