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xaskasdf/llm-compiler-13b-ftd-gguf
llm-compiler-13b-ftd-gguf is a machine learning model from xaskasdf. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
This is a GGUF conversion and quantization of Meta's LLM Compiler 13B FTD model, optimized for code and compiler tasks.
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From the Hugging Face model README
This is a GGUF conversion and quantization of Meta's LLM Compiler 13B FTD model, optimized for code and compiler tasks.
LLM Compiler 13B FTD is part of the LLM Compiler family developed by Meta, designed specifically for code optimization tasks. This GGUF version is a converted and quantized variant of the original model, optimized for use with llama.cpp.
The model is fine-tuned for:
opt to minimize code sizeThis model is intended for commercial and research use in tasks related to compiler optimization, code analysis, and transformation. It excels in tasks such as:
To use this model, you'll need to use llama.cpp or compatible software that can work with GGUF format models. Refer to the llama.cpp documentation for specific usage instructions.
Example prompt formats can be found in the llm_compiler_demo.py file from the original repository.
This model is subject to multiple licenses:
The original model is licensed under the Meta Large Language Model Compiler (LLM Compiler) License Agreement. Key points of this license include:
The GGUF conversion is subject to the MIT License, as it uses llama.cpp for the conversion process.
Usage of the model must comply with the Acceptable Use Policy for Llama Materials.
Commercial use may require additional licensing from Meta. Users are responsible for ensuring their use complies with all applicable licenses and policies.
For full license details and use restrictions, please refer to:
It is strongly recommended to review the full license text and consult with legal counsel if you have any questions about your specific use case.
For more details on the original model's performance, training process, and ethical considerations, please refer to the research paper: "Meta Large Language Model Compiler: Foundation Models of Compiler Optimization"
This GGUF version was created to enable efficient use with llama.cpp and related projects. Performance may differ from the original model due to quantization and format conversion.