Instructions to use taskmaster141/Minicpm-2b_lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use taskmaster141/Minicpm-2b_lora with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("taskmaster141/Minicpm-2b_lora", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
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Download README.md from taskmaster141/Minicpm-2b_lora: direct link, hf CLI and curl.
- Browser
- Download file 533 Bytes
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https://huggingface.co/taskmaster141/Minicpm-2b_lora/resolve/main/README.md
- Command line
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hf download hf://taskmaster141/Minicpm-2b_lora/README.md
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curl -L -o README.md https://huggingface.co/taskmaster141/Minicpm-2b_lora/resolve/main/README.md
533 Bytes
| base_model: openbmb/MiniCPM5-2B | |
| tags: | |
| - text-generation-inference | |
| - transformers | |
| - unsloth | |
| - llama | |
| - trl | |
| license: apache-2.0 | |
| language: | |
| - en | |
| # Uploaded model | |
| - **Developed by:** taskmaster141 | |
| - **License:** apache-2.0 | |
| - **Finetuned from model :** openbmb/MiniCPM5-2B | |
| This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) | |
| [<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth) | |