File size: 5,005 Bytes
6da6fe6 c1bed9d 6da6fe6 94a920d 6da6fe6 94a920d 2fb7058 94a920d 6da6fe6 110e177 6da6fe6 2fb7058 fd57b97 0d6b15b 2e7fd30 1ece0cb 0d6b15b cbc9a3e 1ece0cb 0d6b15b cbc9a3e 0d6b15b 2e7fd30 0d6b15b c4fe375 fd57b97 aca3d1d 7333c42 cbc9a3e c48d3a9 6da6fe6 43a010a 110e177 43a010a 110e177 3b9837f c1bed9d 73728fc 6da6fe6 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 |
---
base_model: cognitivecomputations/Samantha-1.11-70b
datasets:
- ehartford/samantha-data
language:
- en
library_name: transformers
license: llama2
quantized_by: mradermacher
---
## About
weighted/imatrix quants of https://huggingface.co/cognitivecomputations/Samantha-1.11-70b
<!-- 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-1.11-70b-i1-GGUF/resolve/main/Samantha-1.11-70b.i1-IQ1_S.gguf) | i1-IQ1_S | 15.0 | for the desperate |
| [GGUF](https://huggingface.co/mradermacher/Samantha-1.11-70b-i1-GGUF/resolve/main/Samantha-1.11-70b.i1-IQ1_M.gguf) | i1-IQ1_M | 16.4 | mostly desperate |
| [GGUF](https://huggingface.co/mradermacher/Samantha-1.11-70b-i1-GGUF/resolve/main/Samantha-1.11-70b.i1-IQ2_XXS.gguf) | i1-IQ2_XXS | 18.7 | |
| [GGUF](https://huggingface.co/mradermacher/Samantha-1.11-70b-i1-GGUF/resolve/main/Samantha-1.11-70b.i1-IQ2_XS.gguf) | i1-IQ2_XS | 20.8 | |
| [GGUF](https://huggingface.co/mradermacher/Samantha-1.11-70b-i1-GGUF/resolve/main/Samantha-1.11-70b.i1-IQ2_S.gguf) | i1-IQ2_S | 21.8 | |
| [GGUF](https://huggingface.co/mradermacher/Samantha-1.11-70b-i1-GGUF/resolve/main/Samantha-1.11-70b.i1-IQ2_M.gguf) | i1-IQ2_M | 23.7 | |
| [GGUF](https://huggingface.co/mradermacher/Samantha-1.11-70b-i1-GGUF/resolve/main/Samantha-1.11-70b.i1-Q2_K.gguf) | i1-Q2_K | 25.9 | IQ3_XXS probably better |
| [GGUF](https://huggingface.co/mradermacher/Samantha-1.11-70b-i1-GGUF/resolve/main/Samantha-1.11-70b.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 27.4 | lower quality |
| [GGUF](https://huggingface.co/mradermacher/Samantha-1.11-70b-i1-GGUF/resolve/main/Samantha-1.11-70b.i1-IQ3_XS.gguf) | i1-IQ3_XS | 28.6 | |
| [GGUF](https://huggingface.co/mradermacher/Samantha-1.11-70b-i1-GGUF/resolve/main/Samantha-1.11-70b.i1-Q3_K_XS.gguf) | i1-Q3_K_XS | 28.7 | |
| [GGUF](https://huggingface.co/mradermacher/Samantha-1.11-70b-i1-GGUF/resolve/main/Samantha-1.11-70b.i1-IQ3_S.gguf) | i1-IQ3_S | 30.3 | beats Q3_K* |
| [GGUF](https://huggingface.co/mradermacher/Samantha-1.11-70b-i1-GGUF/resolve/main/Samantha-1.11-70b.i1-Q3_K_S.gguf) | i1-Q3_K_S | 30.3 | IQ3_XS probably better |
| [GGUF](https://huggingface.co/mradermacher/Samantha-1.11-70b-i1-GGUF/resolve/main/Samantha-1.11-70b.i1-IQ3_M.gguf) | i1-IQ3_M | 31.4 | |
| [GGUF](https://huggingface.co/mradermacher/Samantha-1.11-70b-i1-GGUF/resolve/main/Samantha-1.11-70b.i1-Q3_K_M.gguf) | i1-Q3_K_M | 33.7 | IQ3_S probably better |
| [GGUF](https://huggingface.co/mradermacher/Samantha-1.11-70b-i1-GGUF/resolve/main/Samantha-1.11-70b.i1-Q3_K_L.gguf) | i1-Q3_K_L | 36.6 | IQ3_M probably better |
| [GGUF](https://huggingface.co/mradermacher/Samantha-1.11-70b-i1-GGUF/resolve/main/Samantha-1.11-70b.i1-IQ4_XS.gguf) | i1-IQ4_XS | 37.2 | |
| [GGUF](https://huggingface.co/mradermacher/Samantha-1.11-70b-i1-GGUF/resolve/main/Samantha-1.11-70b.i1-IQ4_NL.gguf) | i1-IQ4_NL | 39.4 | prefer IQ4_XS |
| [GGUF](https://huggingface.co/mradermacher/Samantha-1.11-70b-i1-GGUF/resolve/main/Samantha-1.11-70b.i1-Q4_0.gguf) | i1-Q4_0 | 39.4 | fast, low quality |
| [GGUF](https://huggingface.co/mradermacher/Samantha-1.11-70b-i1-GGUF/resolve/main/Samantha-1.11-70b.i1-Q4_K_S.gguf) | i1-Q4_K_S | 39.7 | optimal size/speed/quality |
| [GGUF](https://huggingface.co/mradermacher/Samantha-1.11-70b-i1-GGUF/resolve/main/Samantha-1.11-70b.i1-Q4_K_M.gguf) | i1-Q4_K_M | 41.8 | fast, recommended |
| [GGUF](https://huggingface.co/mradermacher/Samantha-1.11-70b-i1-GGUF/resolve/main/Samantha-1.11-70b.i1-Q5_K_S.gguf) | i1-Q5_K_S | 47.9 | |
| [GGUF](https://huggingface.co/mradermacher/Samantha-1.11-70b-i1-GGUF/resolve/main/Samantha-1.11-70b.i1-Q5_K_M.gguf) | i1-Q5_K_M | 49.2 | |
| [PART 1](https://huggingface.co/mradermacher/Samantha-1.11-70b-i1-GGUF/resolve/main/Samantha-1.11-70b.i1-Q6_K.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/Samantha-1.11-70b-i1-GGUF/resolve/main/Samantha-1.11-70b.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):
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.
<!-- end -->
|