Instructions to use OL-OL/lora_model_graph_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OL-OL/lora_model_graph_test with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("OL-OL/lora_model_graph_test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
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Download README.md from OL-OL/lora_model_graph_test: direct link, hf CLI and curl.
- Browser
- Download file 432 Bytes
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https://huggingface.co/OL-OL/lora_model_graph_test/resolve/main/README.md
- Command line
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hf download hf://OL-OL/lora_model_graph_test/README.md
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curl -L -o README.md https://huggingface.co/OL-OL/lora_model_graph_test/resolve/main/README.md
432 Bytes
| base_model: unsloth/Llama-3.2-11B-Vision-Instruct | |
| tags: | |
| - text-generation-inference | |
| - transformers | |
| - unsloth | |
| - mllama | |
| - trl | |
| license: apache-2.0 | |
| language: | |
| - en | |
| # Uploaded model | |
| - **Developed by:** OL-OL | |
| - **License:** apache-2.0 | |
| - **Finetuned from model :** unsloth/Llama-3.2-11B-Vision-Instruct | |
| This mllama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library. | |