Image-to-Text
Transformers
PyTorch
English
llava
text-generation
visual-question-answering
image-captioning
Instructions to use kaist-ai/volcano-7b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kaist-ai/volcano-7b 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="kaist-ai/volcano-7b")# Load model directly from transformers import AutoProcessor, AutoModelForCausalLM processor = AutoProcessor.from_pretrained("kaist-ai/volcano-7b") model = AutoModelForCausalLM.from_pretrained("kaist-ai/volcano-7b", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 91bf184ab12793d0754344f9095332759432e666320cc6c07f637af50e36db6f
- Size of remote file:
- 500 kB
- SHA256:
- 9e556afd44213b6bd1be2b850ebbbd98f5481437a8021afaf58ee7fb1818d347
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