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---
base_model: unsloth/llama-3-70b-Instruct-bnb-4bit
exported_from: Dogge/llama-3-70B-instruct-uncensored
language:
- en
library_name: transformers
license: apache-2.0
no_imatrix: 'GGML_ASSERT: llama.cpp/ggml-quants.c:11239: grid_index >= 0'
quantized_by: mradermacher
tags:
- text-generation-inference
- transformers
- unsloth
- llama
- trl
- sft
---
## About
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weighted/imatrix quants of https://huggingface.co/Dogge/llama-3-70B-instruct-uncensored
**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/llama-3-70B-instruct-uncensored-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/llama-3-70B-instruct-uncensored-i1-GGUF/resolve/main/llama-3-70B-instruct-uncensored.i1-Q2_K.gguf) | i1-Q2_K | 26.5 | IQ3_XXS probably better |
| [GGUF](https://huggingface.co/mradermacher/llama-3-70B-instruct-uncensored-i1-GGUF/resolve/main/llama-3-70B-instruct-uncensored.i1-Q3_K_S.gguf) | i1-Q3_K_S | 31.0 | IQ3_XS probably better |
| [GGUF](https://huggingface.co/mradermacher/llama-3-70B-instruct-uncensored-i1-GGUF/resolve/main/llama-3-70B-instruct-uncensored.i1-Q3_K_M.gguf) | i1-Q3_K_M | 34.4 | IQ3_S probably better |
| [GGUF](https://huggingface.co/mradermacher/llama-3-70B-instruct-uncensored-i1-GGUF/resolve/main/llama-3-70B-instruct-uncensored.i1-Q3_K_L.gguf) | i1-Q3_K_L | 37.2 | IQ3_M probably better |
| [GGUF](https://huggingface.co/mradermacher/llama-3-70B-instruct-uncensored-i1-GGUF/resolve/main/llama-3-70B-instruct-uncensored.i1-Q4_K_S.gguf) | i1-Q4_K_S | 40.4 | optimal size/speed/quality |
| [GGUF](https://huggingface.co/mradermacher/llama-3-70B-instruct-uncensored-i1-GGUF/resolve/main/llama-3-70B-instruct-uncensored.i1-Q4_K_M.gguf) | i1-Q4_K_M | 42.6 | fast, recommended |
| [GGUF](https://huggingface.co/mradermacher/llama-3-70B-instruct-uncensored-i1-GGUF/resolve/main/llama-3-70B-instruct-uncensored.i1-Q5_K_S.gguf) | i1-Q5_K_S | 48.8 | |
| [PART 1](https://huggingface.co/mradermacher/llama-3-70B-instruct-uncensored-i1-GGUF/resolve/main/llama-3-70B-instruct-uncensored.i1-Q6_K.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/llama-3-70B-instruct-uncensored-i1-GGUF/resolve/main/llama-3-70B-instruct-uncensored.i1-Q6_K.gguf.part2of2) | i1-Q6_K | 58.0 | 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
## 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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