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 processor_config.json from hf-internal-testing/tiny-random-Blip2ForConditionalGeneration: direct link, hf CLI and curl.
- Browser
- Download file 68 Bytes
-
https://huggingface.co/hf-internal-testing/tiny-random-Blip2ForConditionalGeneration/resolve/d0de11fd1f8ca481231c07ee0934924be96cb281/processor_config.json
- Command line
-
hf download hf://hf-internal-testing/tiny-random-Blip2ForConditionalGeneration@d0de11fd1f8ca481231c07ee0934924be96cb281/processor_config.json
-
curl -L -o processor_config.json https://huggingface.co/hf-internal-testing/tiny-random-Blip2ForConditionalGeneration/resolve/d0de11fd1f8ca481231c07ee0934924be96cb281/processor_config.json
68 Bytes
| { | |
| "num_query_tokens": 10, | |
| "processor_class": "Blip2Processor" | |
| } | |