auto-patch README.md

This commit is contained in:
team mradermacher
2026-01-11 01:25:04 +00:00
committed by system
parent 7a59fdb552
commit bc31a57cd4

View File

@@ -1,3 +1,26 @@
---
base_model: midorin-Linux/gpt-oss-20b-Coding-Distill
datasets:
- TeichAI/gpt-5.2-high-reasoning-250x
- TeichAI/gpt-5.1-codex-max-1000x
- TeichAI/claude-4.5-opus-high-reasoning-250x
- TeichAI/claude-sonnet-4.5-high-reasoning-250x
language:
- en
library_name: transformers
license: apache-2.0
mradermacher:
readme_rev: 1
quantized_by: mradermacher
tags:
- gpt_oss
- openai
- unsloth
- conversational
- code
---
## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
@@ -7,3 +30,52 @@
<!-- ### quants_skip: -->
<!-- ### skip_mmproj: -->
weighted/imatrix quants of https://huggingface.co/midorin-Linux/gpt-oss-20b-Coding-Distill
<!-- provided-files -->
***For a convenient overview and download list, visit our [model page for this model](https://hf.tst.eu/model#gpt-oss-20b-Coding-Distill-i1-GGUF).***
static quants are available at https://huggingface.co/mradermacher/gpt-oss-20b-Coding-Distill-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/gpt-oss-20b-Coding-Distill-i1-GGUF/resolve/main/gpt-oss-20b-Coding-Distill.imatrix.gguf) | imatrix | 0.1 | imatrix file (for creating your own quants) |
| [GGUF](https://huggingface.co/mradermacher/gpt-oss-20b-Coding-Distill-i1-GGUF/resolve/main/gpt-oss-20b-Coding-Distill.i1-IQ2_M.gguf) | i1-IQ2_M | 12.2 | |
| [GGUF](https://huggingface.co/mradermacher/gpt-oss-20b-Coding-Distill-i1-GGUF/resolve/main/gpt-oss-20b-Coding-Distill.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 12.2 | lower quality |
| [GGUF](https://huggingface.co/mradermacher/gpt-oss-20b-Coding-Distill-i1-GGUF/resolve/main/gpt-oss-20b-Coding-Distill.i1-Q2_K.gguf) | i1-Q2_K | 12.2 | IQ3_XXS probably better |
| [GGUF](https://huggingface.co/mradermacher/gpt-oss-20b-Coding-Distill-i1-GGUF/resolve/main/gpt-oss-20b-Coding-Distill.i1-IQ4_XS.gguf) | i1-IQ4_XS | 12.2 | |
| [GGUF](https://huggingface.co/mradermacher/gpt-oss-20b-Coding-Distill-i1-GGUF/resolve/main/gpt-oss-20b-Coding-Distill.i1-IQ3_M.gguf) | i1-IQ3_M | 12.3 | |
| [GGUF](https://huggingface.co/mradermacher/gpt-oss-20b-Coding-Distill-i1-GGUF/resolve/main/gpt-oss-20b-Coding-Distill.i1-Q3_K_M.gguf) | i1-Q3_K_M | 13.0 | IQ3_S probably better |
| [GGUF](https://huggingface.co/mradermacher/gpt-oss-20b-Coding-Distill-i1-GGUF/resolve/main/gpt-oss-20b-Coding-Distill.i1-Q4_K_S.gguf) | i1-Q4_K_S | 14.8 | optimal size/speed/quality |
| [GGUF](https://huggingface.co/mradermacher/gpt-oss-20b-Coding-Distill-i1-GGUF/resolve/main/gpt-oss-20b-Coding-Distill.i1-Q4_K_M.gguf) | i1-Q4_K_M | 15.9 | fast, recommended |
| [GGUF](https://huggingface.co/mradermacher/gpt-oss-20b-Coding-Distill-i1-GGUF/resolve/main/gpt-oss-20b-Coding-Distill.i1-Q6_K.gguf) | i1-Q6_K | 22.3 | practically like static Q6_K |
Here is a handy graph by ikawrakow comparing some lower-quality quant
types (lower is better):
![image.png](https://www.nethype.de/huggingface_embed/quantpplgraph.png)
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.
<!-- end -->