base_model: ibm-granite/granite-20b-code-instruct
datasets:
- bigcode/commitpackft
- TIGER-Lab/MathInstruct
- meta-math/MetaMathQA
- glaiveai/glaive-code-assistant-v3
- glaive-function-calling-v2
- bugdaryan/sql-create-context-instruction
- garage-bAInd/Open-Platypus
- nvidia/HelpSteer
language:
- en
library_name: transformers
license: apache-2.0
quantized_by: mradermacher
tags:
- code
- granite
About
weighted/imatrix quants of https://huggingface.co/ibm-granite/granite-20b-code-instruct
static quants are available at https://huggingface.co/mradermacher/granite-20b-code-instruct-GGUF
Usage
If you are unsure how to use GGUF files, refer to one of TheBloke's READMEs for more details, including on how to concatenate multi-part files.
Provided Quants
(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)
Link | Type | Size/GB | Notes |
---|---|---|---|
GGUF | i1-IQ1_S | 4.6 | for the desperate |
GGUF | i1-IQ1_M | 5.0 | mostly desperate |
GGUF | i1-IQ2_XXS | 5.7 | |
GGUF | i1-IQ2_XS | 6.3 | |
GGUF | i1-IQ2_S | 6.6 | |
GGUF | i1-IQ2_M | 7.2 | |
GGUF | i1-Q2_K | 8.0 | IQ3_XXS probably better |
GGUF | i1-IQ3_XXS | 8.2 | lower quality |
GGUF | i1-IQ3_XS | 8.8 | |
GGUF | i1-IQ3_S | 9.0 | beats Q3_K* |
GGUF | i1-Q3_K_S | 9.0 | IQ3_XS probably better |
GGUF | i1-IQ3_M | 9.7 | |
GGUF | i1-Q3_K_M | 10.7 | IQ3_S probably better |
GGUF | i1-IQ4_XS | 11.0 | |
GGUF | i1-Q4_0 | 11.7 | fast, low quality |
GGUF | i1-Q4_K_S | 11.8 | optimal size/speed/quality |
GGUF | i1-Q3_K_L | 11.8 | IQ3_M probably better |
GGUF | i1-Q4_K_M | 12.9 | fast, recommended |
GGUF | i1-Q5_K_S | 14.1 | |
GGUF | i1-Q5_K_M | 14.9 | |
GGUF | i1-Q6_K | 16.7 | practically like static Q6_K |
Here is a handy graph by ikawrakow comparing some lower-quality quant types (lower is better):
And here are Artefact2's thoughts on the matter: https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9
FAQ / Model Request
See https://huggingface.co/mradermacher/model_requests for some answers to questions you might have and/or if you want some other model quantized.
Thanks
I thank my company, nethype GmbH, for letting me use its servers and providing upgrades to my workstation to enable this work in my free time. Additional thanks to @nicoboss for giving me access to his private supercomputer, enabling me to provide many more imatrix quants, at much higher quality, than I would otherwise be able to.