Instructions to use eltorio/Llama-3.2-3B-appreciation-F16-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use eltorio/Llama-3.2-3B-appreciation-F16-GGUF with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
Upload README.md with huggingface_hub
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README.md
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tags:
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- llama-cpp
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- gguf-my-lora
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pipeline_tag: text2text-generation
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---
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# eltorio/Llama-3.2-3B-appreciation-F16-GGUF
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## Use with llama.cpp
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- Download the [base model in GGUF format](https://huggingface.co/bartowski/Llama-3.2-3B-Instruct-GGUF/blob/main/Llama-3.2-3B-Instruct-f16.gguf)
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- Download the [LoRa adapter in GGUF format](https://huggingface.co/eltorio/Llama-3.2-3B-appreciation-F16-GGUF/blob/main/Llama-3.2-3B-appreciation-f16.gguf)
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```bash
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# with cli
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llama-cli -
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# with server
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llama-
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```
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To know more about LoRA usage with llama.cpp server, refer to the [llama.cpp server documentation](https://github.com/ggerganov/llama.cpp/blob/master/examples/server/README.md).
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tags:
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- llama-cpp
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- gguf-my-lora
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---
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# eltorio/Llama-3.2-3B-appreciation-F16-GGUF
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## Use with llama.cpp
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```bash
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# with cli
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llama-cli -m base_model.gguf --lora Llama-3.2-3B-appreciation-f16.gguf (...other args)
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# with server
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llama-server -m base_model.gguf --lora Llama-3.2-3B-appreciation-f16.gguf (...other args)
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```
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To know more about LoRA usage with llama.cpp server, refer to the [llama.cpp server documentation](https://github.com/ggerganov/llama.cpp/blob/master/examples/server/README.md).
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