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grok-1-GGUF
mradermacher/grok-1-GGUF
grok-1-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 apache-2.0.
static quants of https://huggingface.co/xai-org/grok-1
Access
Public
Updated Sep 7, 2024
Repo size
2.6 TB
Likes
4
Public
Repo makeup
Click a slice to open those files.
.part1of3224 GB · 9%
At a glance
- Library
- transformers
- License
- apache-2.0
- Access
- Public
- Created
- Sep 2, 2024
- Updated
- Sep 7, 2024
- SHA
- 2cc15404
Base models
Model card
From the Hugging Face model README
About
<!-- ### quantize_version: 2 --> <!-- ### output_tensor_quantised: 1 --> <!-- ### convert_type: hf --> <!-- ### vocab_type: --> <!-- ### tags: -->static quants of https://huggingface.co/xai-org/grok-1
<!-- provided-files -->weighted/imatrix quants are available at https://huggingface.co/mradermacher/grok-1-i1-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 |
|---|---|---|---|
| PART 1 PART 2 PART 3 | Q2_K | 116.3 | |
| PART 1 PART 2 PART 3 | IQ3_XS | 130.2 | |
| PART 1 PART 2 PART 3 | IQ3_S | 137.6 | beats Q3_K* |
| PART 1 PART 2 PART 3 | Q3_K_S | 137.6 | |
| PART 1 PART 2 PART 3 | IQ3_M | 144.4 | |
| PART 1 PART 2 PART 3 PART 4 | Q3_K_M | 152.1 | lower quality |
| PART 1 PART 2 PART 3 PART 4 | Q3_K_L | 163.5 | |
| PART 1 PART 2 PART 3 PART 4 | IQ4_XS | 171.3 | |
| PART 1 PART 2 PART 3 PART 4 | Q4_K_S | 180.7 | fast, recommended |
| PART 1 PART 2 PART 3 PART 4 | Q4_K_M | 192.3 | fast, recommended |
| P1 P2 P3 P4 P5 | Q5_K_S | 218.1 | |
| P1 P2 P3 P4 P5 | Q5_K_M | 225.0 | |
| P1 P2 P3 P4 P5 P6 | Q6_K | 259.9 | very good quality |
| P1 P2 P3 P4 P5 P6 P7 | Q8_0 | 336.4 | 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
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.
<!-- end -->- Library
- transformers
- License
- apache-2.0
- Languages
- en
- Created
- Sep 2, 2024
- Updated
- Sep 7, 2024