Instructions to use hf-internal-testing/tiny-random-Blip2Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-Blip2Model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-Blip2Model")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-Blip2Model") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-Blip2Model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cae10de8675eb81b6886afbb5ecf33a21e9893b0b6aa187a1b7ef585338bd9d5
- Size of remote file:
- 965 kB
- SHA256:
- a20e40c69c5a6f720e52c500055ec2d754c115c7acf597499e27e82e96a1384c
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