metadata
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
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 | 32.7 | |
| GGUF | i1-IQ2_XXS | 41.2 | |
| GGUF | i1-IQ2_XS | 45.8 | |
| PART 1 PART 2 | i1-Q2_K | 57.0 | IQ3_XXS probably better |
| PART 1 PART 2 | i1-IQ3_XXS | 60.5 | fast, lower quality |
| PART 1 PART 2 | i1-Q3_K_XS | 63.1 | |
| PART 1 PART 2 | i1-Q3_K_S | 66.8 | IQ3_XS probably better |
| PART 1 PART 2 | i1-Q3_K_M | 74.6 | IQ3_S probably better |
| PART 1 PART 2 | i1-Q3_K_L | 81.2 | IQ3_M probably better |
| PART 1 PART 2 | i1-Q4_K_S | 88.0 | almost as good as Q4_K_M |
| PART 1 PART 2 | 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):
And here are Artefact2's thoughts on the matter: https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9