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---
base_model: Spestly/Atlas-Pro-7B-Preview
datasets:
- openai/gsm8k
- HuggingFaceH4/ultrachat_200k
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
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: nicoboss -->
weighted/imatrix quants of https://huggingface.co./Spestly/Atlas-Pro-7B-Preview
<!-- provided-files -->
static quants are available at https://huggingface.co./mradermacher/Atlas-Pro-7B-Preview-GGUF
## Usage
If you are unsure how to use GGUF files, refer to one of [TheBloke's
READMEs](https://huggingface.co./TheBloke/KafkaLM-70B-German-V0.1-GGUF) 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](https://huggingface.co./mradermacher/Atlas-Pro-7B-Preview-i1-GGUF/resolve/main/Atlas-Pro-7B-Preview.i1-IQ1_S.gguf) | i1-IQ1_S | 2.0 | for the desperate |
| [GGUF](https://huggingface.co./mradermacher/Atlas-Pro-7B-Preview-i1-GGUF/resolve/main/Atlas-Pro-7B-Preview.i1-IQ1_M.gguf) | i1-IQ1_M | 2.1 | mostly desperate |
| [GGUF](https://huggingface.co./mradermacher/Atlas-Pro-7B-Preview-i1-GGUF/resolve/main/Atlas-Pro-7B-Preview.i1-IQ2_XXS.gguf) | i1-IQ2_XXS | 2.4 | |
| [GGUF](https://huggingface.co./mradermacher/Atlas-Pro-7B-Preview-i1-GGUF/resolve/main/Atlas-Pro-7B-Preview.i1-IQ2_XS.gguf) | i1-IQ2_XS | 2.6 | |
| [GGUF](https://huggingface.co./mradermacher/Atlas-Pro-7B-Preview-i1-GGUF/resolve/main/Atlas-Pro-7B-Preview.i1-IQ2_S.gguf) | i1-IQ2_S | 2.7 | |
| [GGUF](https://huggingface.co./mradermacher/Atlas-Pro-7B-Preview-i1-GGUF/resolve/main/Atlas-Pro-7B-Preview.i1-IQ2_M.gguf) | i1-IQ2_M | 2.9 | |
| [GGUF](https://huggingface.co./mradermacher/Atlas-Pro-7B-Preview-i1-GGUF/resolve/main/Atlas-Pro-7B-Preview.i1-Q2_K_S.gguf) | i1-Q2_K_S | 2.9 | very low quality |
| [GGUF](https://huggingface.co./mradermacher/Atlas-Pro-7B-Preview-i1-GGUF/resolve/main/Atlas-Pro-7B-Preview.i1-Q2_K.gguf) | i1-Q2_K | 3.1 | IQ3_XXS probably better |
| [GGUF](https://huggingface.co./mradermacher/Atlas-Pro-7B-Preview-i1-GGUF/resolve/main/Atlas-Pro-7B-Preview.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 3.2 | lower quality |
| [GGUF](https://huggingface.co./mradermacher/Atlas-Pro-7B-Preview-i1-GGUF/resolve/main/Atlas-Pro-7B-Preview.i1-IQ3_XS.gguf) | i1-IQ3_XS | 3.4 | |
| [GGUF](https://huggingface.co./mradermacher/Atlas-Pro-7B-Preview-i1-GGUF/resolve/main/Atlas-Pro-7B-Preview.i1-Q3_K_S.gguf) | i1-Q3_K_S | 3.6 | IQ3_XS probably better |
| [GGUF](https://huggingface.co./mradermacher/Atlas-Pro-7B-Preview-i1-GGUF/resolve/main/Atlas-Pro-7B-Preview.i1-IQ3_S.gguf) | i1-IQ3_S | 3.6 | beats Q3_K* |
| [GGUF](https://huggingface.co./mradermacher/Atlas-Pro-7B-Preview-i1-GGUF/resolve/main/Atlas-Pro-7B-Preview.i1-IQ3_M.gguf) | i1-IQ3_M | 3.7 | |
| [GGUF](https://huggingface.co./mradermacher/Atlas-Pro-7B-Preview-i1-GGUF/resolve/main/Atlas-Pro-7B-Preview.i1-Q3_K_M.gguf) | i1-Q3_K_M | 3.9 | IQ3_S probably better |
| [GGUF](https://huggingface.co./mradermacher/Atlas-Pro-7B-Preview-i1-GGUF/resolve/main/Atlas-Pro-7B-Preview.i1-Q3_K_L.gguf) | i1-Q3_K_L | 4.2 | IQ3_M probably better |
| [GGUF](https://huggingface.co./mradermacher/Atlas-Pro-7B-Preview-i1-GGUF/resolve/main/Atlas-Pro-7B-Preview.i1-IQ4_XS.gguf) | i1-IQ4_XS | 4.3 | |
| [GGUF](https://huggingface.co./mradermacher/Atlas-Pro-7B-Preview-i1-GGUF/resolve/main/Atlas-Pro-7B-Preview.i1-IQ4_NL.gguf) | i1-IQ4_NL | 4.5 | prefer IQ4_XS |
| [GGUF](https://huggingface.co./mradermacher/Atlas-Pro-7B-Preview-i1-GGUF/resolve/main/Atlas-Pro-7B-Preview.i1-Q4_0.gguf) | i1-Q4_0 | 4.5 | fast, low quality |
| [GGUF](https://huggingface.co./mradermacher/Atlas-Pro-7B-Preview-i1-GGUF/resolve/main/Atlas-Pro-7B-Preview.i1-Q4_K_S.gguf) | i1-Q4_K_S | 4.6 | optimal size/speed/quality |
| [GGUF](https://huggingface.co./mradermacher/Atlas-Pro-7B-Preview-i1-GGUF/resolve/main/Atlas-Pro-7B-Preview.i1-Q4_K_M.gguf) | i1-Q4_K_M | 4.8 | fast, recommended |
| [GGUF](https://huggingface.co./mradermacher/Atlas-Pro-7B-Preview-i1-GGUF/resolve/main/Atlas-Pro-7B-Preview.i1-Q4_1.gguf) | i1-Q4_1 | 5.0 | |
| [GGUF](https://huggingface.co./mradermacher/Atlas-Pro-7B-Preview-i1-GGUF/resolve/main/Atlas-Pro-7B-Preview.i1-Q5_K_S.gguf) | i1-Q5_K_S | 5.4 | |
| [GGUF](https://huggingface.co./mradermacher/Atlas-Pro-7B-Preview-i1-GGUF/resolve/main/Atlas-Pro-7B-Preview.i1-Q5_K_M.gguf) | i1-Q5_K_M | 5.5 | |
| [GGUF](https://huggingface.co./mradermacher/Atlas-Pro-7B-Preview-i1-GGUF/resolve/main/Atlas-Pro-7B-Preview.i1-Q6_K.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](https://www.nethype.de/), for letting
me use its servers and providing upgrades to my workstation to enable
this work in my free time. Additional thanks to [@nicoboss](https://huggingface.co./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.
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