Image-to-Text
Transformers
Safetensors
English
blip-2
visual-question-answering
vision
image-captioning
Instructions to use anonymoussubmission2024/vlrm-blip2-opt-2.7b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anonymoussubmission2024/vlrm-blip2-opt-2.7b 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="anonymoussubmission2024/vlrm-blip2-opt-2.7b")# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("anonymoussubmission2024/vlrm-blip2-opt-2.7b") model = AutoModelForMultimodalLM.from_pretrained("anonymoussubmission2024/vlrm-blip2-opt-2.7b") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 543779a998775e593dc9eed1e61c243b445015dc7d5186d10a4543aeef7c8df9
- Size of remote file:
- 1.52 GB
- SHA256:
- fb1dc8537989597f746b5d8dfdeb42e3a29326807c7b627b28caa2d13313f875
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