|
--- |
|
datasets: |
|
- ehartford/samantha-data |
|
language: |
|
- en |
|
library_name: transformers |
|
license: llama2 |
|
quantized_by: mradermacher |
|
--- |
|
## About |
|
|
|
weighted/imatrix quants of https://huggingface.co/cognitivecomputations/Samantha-1.1-70b |
|
|
|
The weights were calculated using 164k semi-random english tokens. |
|
|
|
<!-- provided-files --> |
|
## 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/Samantha-1.1-70b-i1-GGUF/resolve/main/Samantha-1.1-70b.i1-IQ1_S.gguf) | i1-IQ1_S | 15.0 | for the desperate | |
|
| [GGUF](https://huggingface.co/mradermacher/Samantha-1.1-70b-i1-GGUF/resolve/main/Samantha-1.1-70b.i1-IQ2_XXS.gguf) | i1-IQ2_XXS | 18.7 | | |
|
| [GGUF](https://huggingface.co/mradermacher/Samantha-1.1-70b-i1-GGUF/resolve/main/Samantha-1.1-70b.i1-IQ2_XS.gguf) | i1-IQ2_XS | 20.8 | | |
|
| [GGUF](https://huggingface.co/mradermacher/Samantha-1.1-70b-i1-GGUF/resolve/main/Samantha-1.1-70b.i1-IQ2_S.gguf) | i1-IQ2_S | 21.8 | | |
|
| [GGUF](https://huggingface.co/mradermacher/Samantha-1.1-70b-i1-GGUF/resolve/main/Samantha-1.1-70b.i1-IQ2_M.gguf) | i1-IQ2_M | 23.7 | | |
|
| [GGUF](https://huggingface.co/mradermacher/Samantha-1.1-70b-i1-GGUF/resolve/main/Samantha-1.1-70b.i1-Q2_K.gguf) | i1-Q2_K | 25.9 | IQ3_XXS probably better | |
|
| [GGUF](https://huggingface.co/mradermacher/Samantha-1.1-70b-i1-GGUF/resolve/main/Samantha-1.1-70b.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 27.4 | lower quality | |
|
| [GGUF](https://huggingface.co/mradermacher/Samantha-1.1-70b-i1-GGUF/resolve/main/Samantha-1.1-70b.i1-IQ3_XS.gguf) | i1-IQ3_XS | 28.6 | | |
|
| [GGUF](https://huggingface.co/mradermacher/Samantha-1.1-70b-i1-GGUF/resolve/main/Samantha-1.1-70b.i1-Q3_K_XS.gguf) | i1-Q3_K_XS | 28.7 | | |
|
| [GGUF](https://huggingface.co/mradermacher/Samantha-1.1-70b-i1-GGUF/resolve/main/Samantha-1.1-70b.i1-IQ3_S.gguf) | i1-IQ3_S | 30.3 | beats Q3_K* | |
|
| [GGUF](https://huggingface.co/mradermacher/Samantha-1.1-70b-i1-GGUF/resolve/main/Samantha-1.1-70b.i1-Q3_K_S.gguf) | i1-Q3_K_S | 30.3 | IQ3_XS probably better | |
|
| [GGUF](https://huggingface.co/mradermacher/Samantha-1.1-70b-i1-GGUF/resolve/main/Samantha-1.1-70b.i1-IQ3_M.gguf) | i1-IQ3_M | 31.4 | | |
|
| [GGUF](https://huggingface.co/mradermacher/Samantha-1.1-70b-i1-GGUF/resolve/main/Samantha-1.1-70b.i1-Q3_K_M.gguf) | i1-Q3_K_M | 33.7 | IQ3_S probably better | |
|
| [GGUF](https://huggingface.co/mradermacher/Samantha-1.1-70b-i1-GGUF/resolve/main/Samantha-1.1-70b.i1-Q3_K_L.gguf) | i1-Q3_K_L | 36.6 | IQ3_M probably better | |
|
| [GGUF](https://huggingface.co/mradermacher/Samantha-1.1-70b-i1-GGUF/resolve/main/Samantha-1.1-70b.i1-Q4_K_S.gguf) | i1-Q4_K_S | 39.7 | optimal size/speed/quality | |
|
| [GGUF](https://huggingface.co/mradermacher/Samantha-1.1-70b-i1-GGUF/resolve/main/Samantha-1.1-70b.i1-Q4_K_M.gguf) | i1-Q4_K_M | 41.8 | fast, recommended | |
|
| [GGUF](https://huggingface.co/mradermacher/Samantha-1.1-70b-i1-GGUF/resolve/main/Samantha-1.1-70b.i1-Q5_K_S.gguf) | i1-Q5_K_S | 47.9 | | |
|
| [GGUF](https://huggingface.co/mradermacher/Samantha-1.1-70b-i1-GGUF/resolve/main/Samantha-1.1-70b.i1-Q5_K_M.gguf) | i1-Q5_K_M | 49.2 | | |
|
| [PART 1](https://huggingface.co/mradermacher/Samantha-1.1-70b-i1-GGUF/resolve/main/Samantha-1.1-70b.i1-Q6_K.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/Samantha-1.1-70b-i1-GGUF/resolve/main/Samantha-1.1-70b.i1-Q6_K.gguf.part2of2) | i1-Q6_K | 57.0 | 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 |
|
|
|
## 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. |
|
|
|
<!-- end --> |
|
|