base_model: cognitivecomputations/dolphin-2.9.1-qwen-110b
datasets:
- cognitivecomputations/Dolphin-2.9
- teknium/OpenHermes-2.5
- m-a-p/CodeFeedback-Filtered-Instruction
- cognitivecomputations/dolphin-coder
- cognitivecomputations/samantha-data
- microsoft/orca-math-word-problems-200k
- Locutusque/function-calling-chatml
- internlm/Agent-FLAN
language:
- en
library_name: transformers
license: other
license_link: https://huggingface.co/Qwen/Qwen1.5-110B/blob/main/LICENSE
license_name: tongyi-qianwen
quantized_by: mradermacher
tags:
- generated_from_trainer
- axolotl
About
weighted/imatrix quants of https://huggingface.co/cognitivecomputations/dolphin-2.9.1-qwen-110b
static quants are available at https://huggingface.co/mradermacher/dolphin-2.9.1-qwen-110b-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 | 23.7 | for the desperate |
| GGUF | i1-IQ1_M | 26.0 | mostly desperate |
| GGUF | i1-IQ2_XXS | 29.9 | |
| GGUF | i1-IQ2_XS | 33.1 | |
| GGUF | i1-IQ2_S | 34.4 | |
| GGUF | i1-IQ2_M | 37.5 | |
| GGUF | i1-Q2_K | 41.3 | IQ3_XXS probably better |
| GGUF | i1-IQ3_XXS | 43.2 | lower quality |
| GGUF | i1-IQ3_XS | 46.0 | |
| GGUF | i1-IQ3_S | 48.6 | beats Q3_K* |
| GGUF | i1-Q3_K_S | 48.6 | IQ3_XS probably better |
| GGUF | i1-IQ3_M | 49.8 | |
| PART 1 PART 2 | i1-Q3_K_M | 53.8 | IQ3_S probably better |
| PART 1 PART 2 | i1-Q3_K_L | 58.2 | IQ3_M probably better |
| PART 1 PART 2 | i1-IQ4_XS | 59.7 | |
| PART 1 PART 2 | i1-Q4_0 | 63.2 | fast, low quality |
| PART 1 PART 2 | i1-Q4_K_S | 63.6 | optimal size/speed/quality |
| PART 1 PART 2 | i1-Q4_K_M | 67.3 | fast, recommended |
| PART 1 PART 2 | i1-Q5_K_S | 76.7 | |
| PART 1 PART 2 | i1-Q5_K_M | 78.9 | |
| PART 1 PART 2 | i1-Q6_K | 91.3 | 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.