Downloads · 30 days
145
8% of all-time downloads
mradermacher/BigWeave-v20-110b-GGUF
BigWeave-v20-110b-GGUF is a machine learning model from mradermacher. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as unknown.
static quants of https://huggingface.co/llmixer/BigWeave-v20-110b
Downloads · 30 days
145
8% of all-time downloads
All-time downloads
1.9K
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.part1of2276 GB · 31%
From the Hugging Face model README
static quants of https://huggingface.co/llmixer/BigWeave-v20-110b
<!-- provided-files -->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.
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.
(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)
| Link | Type | Size/GB | Notes |
|---|---|---|---|
| GGUF | Q2_K | 40.8 | |
| GGUF | IQ3_XS | 45.2 | |
| GGUF | Q3_K_S | 47.8 | |
| GGUF | IQ3_S | 47.9 | beats Q3_K* |
| GGUF | IQ3_M | 49.6 | |
| PART 1 PART 2 | Q3_K_M | 53.3 | lower quality |
| PART 1 PART 2 | Q3_K_L | 58.0 | |
| PART 1 PART 2 | IQ4_XS | 59.7 | |
| PART 1 PART 2 | Q4_K_S | 62.9 | fast, recommended |
| PART 1 PART 2 | Q4_K_M | 66.4 | fast, recommended |
| PART 1 PART 2 | Q5_K_S | 76.1 | |
| PART 1 PART 2 | Q5_K_M | 78.2 | |
| PART 1 PART 2 | Q6_K | 90.7 | very good quality |
| PART 1 PART 2 PART 3 | Q8_0 | 117.3 | fast, best quality |
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
See https://huggingface.co/mradermacher/model_requests for some answers to questions you might have and/or if you want some other model quantized.
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.
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