Instructions to use hf-internal-testing/tiny-random-Blip2ForConditionalGeneration with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/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-internal-testing/tiny-random-Blip2ForConditionalGeneration")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-Blip2ForConditionalGeneration") model = AutoModelForMultimodalLM.from_pretrained("hf-internal-testing/tiny-random-Blip2ForConditionalGeneration", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from hf-internal-testing/tiny-random-Blip2ForConditionalGeneration: direct link, hf CLI and curl.
- Browser
- Download file 965 kB
-
https://huggingface.co/hf-internal-testing/tiny-random-Blip2ForConditionalGeneration/resolve/04b1b54bc268de69f4c3b280e5f6d2d64423d3ee/pytorch_model.bin
- Command line
-
hf download hf://hf-internal-testing/tiny-random-Blip2ForConditionalGeneration@04b1b54bc268de69f4c3b280e5f6d2d64423d3ee/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/hf-internal-testing/tiny-random-Blip2ForConditionalGeneration/resolve/04b1b54bc268de69f4c3b280e5f6d2d64423d3ee/pytorch_model.bin
965 kB
- Xet hash:
- 4e64aa55849e4730465b0885db95d6690475504523f5276f2bc1be1abf3fc917
- Size of remote file:
- 965 kB
- SHA256:
- c82e25ae129cbe44b4fabcbefee62d6bcc15e0d91df135f3ec2137c63ad6383a
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