base_model, datasets, language, library_name, mradermacher, quantized_by, tags
| base_model | datasets | language | library_name | mradermacher | quantized_by | tags | ||||||||||||||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Delta-Vector/Francois-PE-V2-Huali-12B |
|
|
transformers |
|
mradermacher |
|
About
weighted/imatrix quants of https://huggingface.co/Delta-Vector/Francois-PE-V2-Huali-12B
For a convenient overview and download list, visit our model page for this model.
static quants are available at https://huggingface.co/mradermacher/Francois-PE-V2-Huali-12B-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-IQ2_XS | 4.0 | |
| GGUF | i1-IQ3_XS | 5.4 | |
| GGUF | i1-IQ4_XS | 6.8 | |
| GGUF | i1-Q4_K_M | 7.6 | fast, recommended |
| GGUF | i1-Q5_K_M | 8.8 | |
| GGUF | i1-Q6_K | 10.2 | 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.