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metadata
license: mit
license_link: https://huggingface.co/microsoft/wavecoder-ultra-6.7b/blob/main/LICENSE
language:
  - en
library_name: transformers
datasets:
  - humaneval
pipeline_tag: text-generation
tags:
  - code
  - TensorBlock
  - GGUF
metrics:
  - code_eval
base_model: microsoft/wavecoder-ultra-6.7b
TensorBlock

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microsoft/wavecoder-ultra-6.7b - GGUF

This repo contains GGUF format model files for microsoft/wavecoder-ultra-6.7b.

The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4242.

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## Prompt template
<|begin▁of▁sentence|>You are an exceptionally intelligent coding assistant that consistently delivers accurate and reliable responses to user instructions.

@@ Instruction
{prompt}

@@ Response

Model file specification

Filename Quant type File Size Description
wavecoder-ultra-6.7b-Q2_K.gguf Q2_K 2.533 GB smallest, significant quality loss - not recommended for most purposes
wavecoder-ultra-6.7b-Q3_K_S.gguf Q3_K_S 2.949 GB very small, high quality loss
wavecoder-ultra-6.7b-Q3_K_M.gguf Q3_K_M 3.299 GB very small, high quality loss
wavecoder-ultra-6.7b-Q3_K_L.gguf Q3_K_L 3.598 GB small, substantial quality loss
wavecoder-ultra-6.7b-Q4_0.gguf Q4_0 3.826 GB legacy; small, very high quality loss - prefer using Q3_K_M
wavecoder-ultra-6.7b-Q4_K_S.gguf Q4_K_S 3.857 GB small, greater quality loss
wavecoder-ultra-6.7b-Q4_K_M.gguf Q4_K_M 4.082 GB medium, balanced quality - recommended
wavecoder-ultra-6.7b-Q5_0.gguf Q5_0 4.652 GB legacy; medium, balanced quality - prefer using Q4_K_M
wavecoder-ultra-6.7b-Q5_K_S.gguf Q5_K_S 4.652 GB large, low quality loss - recommended
wavecoder-ultra-6.7b-Q5_K_M.gguf Q5_K_M 4.784 GB large, very low quality loss - recommended
wavecoder-ultra-6.7b-Q6_K.gguf Q6_K 5.530 GB very large, extremely low quality loss
wavecoder-ultra-6.7b-Q8_0.gguf Q8_0 7.162 GB very large, extremely low quality loss - not recommended

Downloading instruction

Command line

Firstly, install Huggingface Client

pip install -U "huggingface_hub[cli]"

Then, downoad the individual model file the a local directory

huggingface-cli download tensorblock/wavecoder-ultra-6.7b-GGUF --include "wavecoder-ultra-6.7b-Q2_K.gguf" --local-dir MY_LOCAL_DIR

If you wanna download multiple model files with a pattern (e.g., *Q4_K*gguf), you can try:

huggingface-cli download tensorblock/wavecoder-ultra-6.7b-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'