Image-to-Text
Transformers
PyTorch
Safetensors
English
blip-2
visual-question-answering
vision
image-captioning
8-bit precision
Instructions to use Mediocreatmybest/blip2-opt-6.7b_8bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mediocreatmybest/blip2-opt-6.7b_8bit 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="Mediocreatmybest/blip2-opt-6.7b_8bit")# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("Mediocreatmybest/blip2-opt-6.7b_8bit") model = AutoModelForMultimodalLM.from_pretrained("Mediocreatmybest/blip2-opt-6.7b_8bit", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c1cb21ce4e7ae9f08e5f659feda648139c8786db434c35c30b1f2cae51b585c3
- Size of remote file:
- 5.54 GB
- SHA256:
- 204bd7310c8ff42cca61944f31075a5b2681339a4beb76c883690c665a6ad5b2
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