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---
base_model:
- cognitivecomputations/dolphin-2.2-70b
- WizardLM/WizardMath-70B-V1.0
- migtissera/SynthIA-70B-v1.2b
- epfl-llm/meditron-70b
language:
- en
library_name: transformers
license: llama2
quantized_by: mradermacher
tags:
- mergekit
- merge
---
## About
weighted/imatrix quants of https://huggingface.co/abacusai/TheProfessor-155b
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## 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/TheProfessor-155b-i1-GGUF/resolve/main/TheProfessor-155b.i1-IQ1_S.gguf) | i1-IQ1_S | 32.7 | |
| [GGUF](https://huggingface.co/mradermacher/TheProfessor-155b-i1-GGUF/resolve/main/TheProfessor-155b.i1-IQ2_XXS.gguf) | i1-IQ2_XXS | 41.2 | |
| [GGUF](https://huggingface.co/mradermacher/TheProfessor-155b-i1-GGUF/resolve/main/TheProfessor-155b.i1-IQ2_XS.gguf) | i1-IQ2_XS | 45.8 | |
| [PART 1](https://huggingface.co/mradermacher/TheProfessor-155b-i1-GGUF/resolve/main/TheProfessor-155b.i1-Q2_K.gguf.split-aa) [PART 2](https://huggingface.co/mradermacher/TheProfessor-155b-i1-GGUF/resolve/main/TheProfessor-155b.i1-Q2_K.gguf.split-ab) | i1-Q2_K | 57.0 | IQ3_XXS probably better |
| [PART 1](https://huggingface.co/mradermacher/TheProfessor-155b-i1-GGUF/resolve/main/TheProfessor-155b.i1-IQ3_XXS.gguf.split-aa) [PART 2](https://huggingface.co/mradermacher/TheProfessor-155b-i1-GGUF/resolve/main/TheProfessor-155b.i1-IQ3_XXS.gguf.split-ab) | i1-IQ3_XXS | 60.5 | fast, lower quality |
| [PART 1](https://huggingface.co/mradermacher/TheProfessor-155b-i1-GGUF/resolve/main/TheProfessor-155b.i1-Q3_K_XS.gguf.split-aa) [PART 2](https://huggingface.co/mradermacher/TheProfessor-155b-i1-GGUF/resolve/main/TheProfessor-155b.i1-Q3_K_XS.gguf.split-ab) | i1-Q3_K_XS | 63.1 | |
| [PART 1](https://huggingface.co/mradermacher/TheProfessor-155b-i1-GGUF/resolve/main/TheProfessor-155b.i1-Q3_K_S.gguf.split-aa) [PART 2](https://huggingface.co/mradermacher/TheProfessor-155b-i1-GGUF/resolve/main/TheProfessor-155b.i1-Q3_K_S.gguf.split-ab) | i1-Q3_K_S | 66.8 | IQ3_XS probably better |
| [PART 1](https://huggingface.co/mradermacher/TheProfessor-155b-i1-GGUF/resolve/main/TheProfessor-155b.i1-Q3_K_M.gguf.split-aa) [PART 2](https://huggingface.co/mradermacher/TheProfessor-155b-i1-GGUF/resolve/main/TheProfessor-155b.i1-Q3_K_M.gguf.split-ab) | i1-Q3_K_M | 74.6 | IQ3_S probably better |
| [PART 1](https://huggingface.co/mradermacher/TheProfessor-155b-i1-GGUF/resolve/main/TheProfessor-155b.i1-Q3_K_L.gguf.split-aa) [PART 2](https://huggingface.co/mradermacher/TheProfessor-155b-i1-GGUF/resolve/main/TheProfessor-155b.i1-Q3_K_L.gguf.split-ab) | i1-Q3_K_L | 81.2 | IQ3_M probably better |
| [PART 1](https://huggingface.co/mradermacher/TheProfessor-155b-i1-GGUF/resolve/main/TheProfessor-155b.i1-Q4_K_S.gguf.split-aa) [PART 2](https://huggingface.co/mradermacher/TheProfessor-155b-i1-GGUF/resolve/main/TheProfessor-155b.i1-Q4_K_S.gguf.split-ab) | i1-Q4_K_S | 88.0 | almost as good as Q4_K_M |
| [PART 1](https://huggingface.co/mradermacher/TheProfessor-155b-i1-GGUF/resolve/main/TheProfessor-155b.i1-Q4_K_M.gguf.split-aa) [PART 2](https://huggingface.co/mradermacher/TheProfessor-155b-i1-GGUF/resolve/main/TheProfessor-155b.i1-Q4_K_M.gguf.split-ab) | i1-Q4_K_M | 93.0 | fast, medium quality |
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
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