Instructions to use hf-tiny-model-private/tiny-random-Blip2ForConditionalGeneration with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-Blip2ForConditionalGeneration with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "visual-question-answering" 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("visual-question-answering", model="hf-tiny-model-private/tiny-random-Blip2ForConditionalGeneration")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("hf-tiny-model-private/tiny-random-Blip2ForConditionalGeneration") model = AutoModelForMultimodalLM.from_pretrained("hf-tiny-model-private/tiny-random-Blip2ForConditionalGeneration", device_map="auto") - Notebooks
- Google Colab
- Kaggle