Instructions to use mradermacher/Kimi-K2.7-Code-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mradermacher/Kimi-K2.7-Code-GGUF with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("mradermacher/Kimi-K2.7-Code-GGUF", dtype="auto") - Notebooks
- Google Colab
- Kaggle
About
static quants of https://huggingface.co/moonshotai/Kimi-K2.7-Code
For a convenient overview and download list, visit our model page for this model.
weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.
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 | mmproj-Q8_0 | 0.7 | multi-modal supplement |
| GGUF | mmproj-f16 | 1.1 | multi-modal supplement |
| P1 P2 P3 P4 P5 P6 P7 P8 | Q2_K | 373.0 | |
| P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 | Q3_K_S | 442.2 | |
| P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11 P12 | Q3_K_M | 489.2 | lower quality |
| P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11 | Q3_K_L | 530.6 | |
| P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11 P12 | IQ4_XS | 551.6 | |
| P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11 P12 P13 | Q4_K_S | 582.6 | fast, recommended |
| P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11 P12 P13 | Q4_K_M | 620.7 | fast, recommended |
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.
- Downloads last month
- 320
Model tree for mradermacher/Kimi-K2.7-Code-GGUF
Base model
moonshotai/Kimi-K2.7-Code