Image-to-Text
Transformers
Safetensors
Japanese
llava-chat-vector
text-generation
vision
image-captioning
VQA
Instructions to use toshi456/chat-vector-llava-v1.5-7b-ja with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use toshi456/chat-vector-llava-v1.5-7b-ja 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/chat-vector-llava-v1.5-7b-ja")# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("toshi456/chat-vector-llava-v1.5-7b-ja", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 91bf184ab12793d0754344f9095332759432e666320cc6c07f637af50e36db6f
- Size of remote file:
- 500 kB
- SHA256:
- 9e556afd44213b6bd1be2b850ebbbd98f5481437a8021afaf58ee7fb1818d347
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