---
base_model: ibivibiv/webby_whale_33b_v1
language:
- en
library_name: transformers
license: mit
no_imatrix: 'GGML_ASSERT: llama.cpp/ggml-quants.c:11239: grid_index >= 0'
quantized_by: mradermacher
---
## About

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weighted/imatrix quants of https://huggingface.co/ibivibiv/webby_whale_33b_v1

**No more quants are incoming, as llama.cpp crashes when generating them.**

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static quants are available at https://huggingface.co/mradermacher/webby_whale_33b_v1-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/webby_whale_33b_v1-i1-GGUF/resolve/main/webby_whale_33b_v1.i1-Q2_K.gguf) | i1-Q2_K | 12.5 | IQ3_XXS probably better |
| [GGUF](https://huggingface.co/mradermacher/webby_whale_33b_v1-i1-GGUF/resolve/main/webby_whale_33b_v1.i1-Q3_K_S.gguf) | i1-Q3_K_S | 14.5 | IQ3_XS probably better |
| [GGUF](https://huggingface.co/mradermacher/webby_whale_33b_v1-i1-GGUF/resolve/main/webby_whale_33b_v1.i1-Q3_K_M.gguf) | i1-Q3_K_M | 16.2 | IQ3_S probably better |
| [GGUF](https://huggingface.co/mradermacher/webby_whale_33b_v1-i1-GGUF/resolve/main/webby_whale_33b_v1.i1-Q3_K_L.gguf) | i1-Q3_K_L | 17.7 | IQ3_M probably better |
| [GGUF](https://huggingface.co/mradermacher/webby_whale_33b_v1-i1-GGUF/resolve/main/webby_whale_33b_v1.i1-IQ4_XS.gguf) | i1-IQ4_XS | 18.0 |  |
| [GGUF](https://huggingface.co/mradermacher/webby_whale_33b_v1-i1-GGUF/resolve/main/webby_whale_33b_v1.i1-IQ4_NL.gguf) | i1-IQ4_NL | 19.0 | prefer IQ4_XS |
| [GGUF](https://huggingface.co/mradermacher/webby_whale_33b_v1-i1-GGUF/resolve/main/webby_whale_33b_v1.i1-Q4_K_S.gguf) | i1-Q4_K_S | 19.0 | optimal size/speed/quality |
| [GGUF](https://huggingface.co/mradermacher/webby_whale_33b_v1-i1-GGUF/resolve/main/webby_whale_33b_v1.i1-Q4_K_M.gguf) | i1-Q4_K_M | 20.0 | fast, recommended |
| [GGUF](https://huggingface.co/mradermacher/webby_whale_33b_v1-i1-GGUF/resolve/main/webby_whale_33b_v1.i1-Q5_K_S.gguf) | i1-Q5_K_S | 23.1 |  |
| [GGUF](https://huggingface.co/mradermacher/webby_whale_33b_v1-i1-GGUF/resolve/main/webby_whale_33b_v1.i1-Q5_K_M.gguf) | i1-Q5_K_M | 23.6 |  |
| [GGUF](https://huggingface.co/mradermacher/webby_whale_33b_v1-i1-GGUF/resolve/main/webby_whale_33b_v1.i1-Q6_K.gguf) | i1-Q6_K | 27.5 | 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.

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