Instructions to use MAGAer13/mplug-owl-llama-7b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MAGAer13/mplug-owl-llama-7b with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "image-to-text" 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("image-to-text", model="MAGAer13/mplug-owl-llama-7b")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("MAGAer13/mplug-owl-llama-7b", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from MAGAer13/mplug-owl-llama-7b: direct link, hf CLI and curl.
- Browser
- Download file 14.2 GB
-
https://huggingface.co/MAGAer13/mplug-owl-llama-7b/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://MAGAer13/mplug-owl-llama-7b/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/MAGAer13/mplug-owl-llama-7b/resolve/main/pytorch_model.bin
14.2 GB
- Xet hash:
- 23d2a16729bcaf82f2040088aeff7e1b7316c3522500ce8335c47b3ad0ef8c38
- Size of remote file:
- 14.2 GB
- SHA256:
- fd4717ca7a00e376cb41c30db482b3dc032804ccc44882fa3fc13713fa983fa9
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