5.7 KiB
base_model, datasets, language, library_name, license, license_link, license_name, quantized_by
| base_model | datasets | language | library_name | license | license_link | license_name | quantized_by | ||||||||||||||||||||||||||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| jondurbin/bagel-dpo-20b-v04 |
|
|
transformers | other | https://huggingface.co/internlm/internlm2-20b#open-source-license | internlm2-20b | mradermacher |
About
weighted/imatrix quants of https://huggingface.co/jondurbin/bagel-dpo-20b-v04
This uses only 95k tokens of my standard set, as the model overflowed with more.
static quants are available at https://huggingface.co/mradermacher/bagel-dpo-20b-v04-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 | 5.4 | for the desperate |
| GGUF | i1-IQ1_M | 5.8 | mostly desperate |
| GGUF | i1-IQ2_XXS | 6.4 | |
| GGUF | i1-IQ2_XS | 6.9 | |
| GGUF | i1-IQ2_S | 7.3 | |
| GGUF | i1-IQ2_M | 7.8 | |
| GGUF | i1-Q2_K | 8.3 | IQ3_XXS probably better |
| GGUF | i1-IQ3_XXS | 8.7 | lower quality |
| GGUF | i1-IQ3_XS | 9.1 | |
| GGUF | i1-Q3_K_S | 9.5 | IQ3_XS probably better |
| GGUF | i1-IQ3_S | 9.6 | beats Q3_K* |
| GGUF | i1-IQ3_M | 9.9 | |
| GGUF | i1-Q3_K_M | 10.5 | IQ3_S probably better |
| GGUF | i1-Q3_K_L | 11.3 | IQ3_M probably better |
| GGUF | i1-IQ4_XS | 11.5 | |
| GGUF | i1-Q4_0 | 12.1 | fast, low quality |
| GGUF | i1-Q4_K_S | 12.2 | optimal size/speed/quality |
| GGUF | i1-Q4_K_M | 12.8 | fast, recommended |
| GGUF | i1-Q5_K_S | 14.5 | |
| GGUF | i1-Q5_K_M | 14.8 | |
| GGUF | i1-Q6_K | 17.1 | 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.