Image Feature Extraction
Transformers
Safetensors
internvl_chat
custom_code
4-bit precision
bitsandbytes
Instructions to use failspy/InternVL-Chat-V1-5-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use failspy/InternVL-Chat-V1-5-4bit with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="failspy/InternVL-Chat-V1-5-4bit", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("failspy/InternVL-Chat-V1-5-4bit", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3d2171f65c6db2a953b9dd5ea1992f48e6cfd22d2156ba45f9dbbfd1e00ec73b
- Size of remote file:
- 4.83 GB
- SHA256:
- 24c278fd71ccc27cc16fda1c99564d4cbf79f150221b305e64a980a0c8f76a8f
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