Instructions to use dysen/Llama-3-Instruct-abliteration-LoRA-8B-F16-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dysen/Llama-3-Instruct-abliteration-LoRA-8B-F16-GGUF with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("dysen/Llama-3-Instruct-abliteration-LoRA-8B-F16-GGUF", dtype="auto") - PEFT
How to use dysen/Llama-3-Instruct-abliteration-LoRA-8B-F16-GGUF with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
dysen/Llama-3-Instruct-abliteration-LoRA-8B-F16-GGUF
This LoRA adapter was converted to GGUF format from grimjim/Llama-3-Instruct-abliteration-LoRA-8B via the ggml.ai's GGUF-my-lora space.
Refer to the original adapter repository for more details.
Use with llama.cpp
# with cli
llama-cli -m base_model.gguf --lora Llama-3-Instruct-abliteration-LoRA-8B-f16.gguf (...other args)
# with server
llama-server -m base_model.gguf --lora Llama-3-Instruct-abliteration-LoRA-8B-f16.gguf (...other args)
To know more about LoRA usage with llama.cpp server, refer to the llama.cpp server documentation.
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