base_model: Spestly/Atlas-Pro-7B-Preview-1M
datasets:
- prithivMLmods/PyCodeZone
- bespokelabs/Bespoke-Stratos-17k
- openai/gsm8k
- rubenroy/GammaCorpus-v1-50k-UNFILTERED
extra_gated_fields:
Country: country
Date of Birth: date_picker
I agree to use this model in accordance with all applicable laws and ethical guidelines: checkbox
I agree to use this model under the MIT licence: checkbox
Intended Use:
options:
- Research
- Education
- Personal Development
- Commercial Use
- label: Other
value: other
type: select
Name: text
Organization: text
extra_gated_prompt: >-
By accessing this model, you agree to comply with ethical usage guidelines and
accept full responsibility for its applications. You will not use this model
for harmful, malicious, or illegal activities, and you understand that the
model's use is subject to ongoing monitoring for misuse. This model is
provided 'AS IS' and agreeing to this means that you are responsible for all
the outputs generated by you
language:
- en
- zh
- fr
- es
- pt
- de
- it
- ru
- ja
- ko
- vi
- th
- ar
- fa
- he
- tr
- cs
- pl
- hi
- bn
- ur
- id
- ms
- lo
- my
- ceb
- km
- tl
- nl
library_name: transformers
license: mit
quantized_by: mradermacher
tags:
- text-generation-inference
- transformers
- unsloth
- qwen2
- trl
About
weighted/imatrix quants of https://huggingface.co/Spestly/Atlas-Pro-7B-Preview-1M
static quants are available at https://huggingface.co/mradermacher/Atlas-Pro-7B-Preview-1M-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 | 2.0 | for the desperate |
| GGUF | i1-IQ1_M | 2.1 | mostly desperate |
| GGUF | i1-IQ2_XXS | 2.4 | |
| GGUF | i1-IQ2_XS | 2.6 | |
| GGUF | i1-IQ2_S | 2.7 | |
| GGUF | i1-IQ2_M | 2.9 | |
| GGUF | i1-Q2_K_S | 2.9 | very low quality |
| GGUF | i1-Q2_K | 3.1 | IQ3_XXS probably better |
| GGUF | i1-IQ3_XXS | 3.2 | lower quality |
| GGUF | i1-IQ3_XS | 3.4 | |
| GGUF | i1-Q3_K_S | 3.6 | IQ3_XS probably better |
| GGUF | i1-IQ3_S | 3.6 | beats Q3_K* |
| GGUF | i1-IQ3_M | 3.7 | |
| GGUF | i1-Q3_K_M | 3.9 | IQ3_S probably better |
| GGUF | i1-Q3_K_L | 4.2 | IQ3_M probably better |
| GGUF | i1-IQ4_XS | 4.3 | |
| GGUF | i1-IQ4_NL | 4.5 | prefer IQ4_XS |
| GGUF | i1-Q4_0 | 4.5 | fast, low quality |
| GGUF | i1-Q4_K_S | 4.6 | optimal size/speed/quality |
| GGUF | i1-Q4_K_M | 4.8 | fast, recommended |
| GGUF | i1-Q4_1 | 5.0 | |
| GGUF | i1-Q5_K_S | 5.4 | |
| GGUF | i1-Q5_K_M | 5.5 | |
| GGUF | i1-Q6_K | 6.4 | 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.