transformers gguf code text-generation-inference Information Extraction IE Named Entity Recogniton Event Extraction Relation Extraction LLaMA en dataset:ACE05 dataset:bc5cdr dataset:conll2003 dataset:ncbi_disease dataset:conll2012_ontonotesv5 dataset:rams dataset:tacred dataset:wnut_17 base_model:KaraKaraWitch/HiTZ-GoLLIE-13B-AsSafeTensors base_model:quantized:KaraKaraWitch/HiTZ-GoLLIE-13B-AsSafeTensors license:llama2 endpoints_compatible region:us imatrix
---
base_model: KaraKaraWitch/HiTZ-GoLLIE-13B-AsSafeTensors
datasets:
- ACE05
- bc5cdr
- conll2003
- ncbi_disease
- conll2012_ontonotesv5
- rams
- tacred
- wnut_17
language:
- en
library_name: transformers
license: llama2
tags:
- code
- text-generation-inference
- Information Extraction
- IE
- Named Entity Recogniton
- Event Extraction
- Relation Extraction
- LLaMA
quantized_by: mradermacher
---
## About

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weighted/imatrix quants of https://huggingface.co/KaraKaraWitch/HiTZ-GoLLIE-13B-AsSafeTensors

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static quants are available at https://huggingface.co/mradermacher/HiTZ-GoLLIE-13B-AsSafeTensors-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/HiTZ-GoLLIE-13B-AsSafeTensors-i1-GGUF/resolve/main/HiTZ-GoLLIE-13B-AsSafeTensors.i1-IQ1_S.gguf) | i1-IQ1_S | 3.0 | for the desperate |
| [GGUF](https://huggingface.co/mradermacher/HiTZ-GoLLIE-13B-AsSafeTensors-i1-GGUF/resolve/main/HiTZ-GoLLIE-13B-AsSafeTensors.i1-IQ1_M.gguf) | i1-IQ1_M | 3.2 | mostly desperate |
| [GGUF](https://huggingface.co/mradermacher/HiTZ-GoLLIE-13B-AsSafeTensors-i1-GGUF/resolve/main/HiTZ-GoLLIE-13B-AsSafeTensors.i1-IQ2_XXS.gguf) | i1-IQ2_XXS | 3.6 |  |
| [GGUF](https://huggingface.co/mradermacher/HiTZ-GoLLIE-13B-AsSafeTensors-i1-GGUF/resolve/main/HiTZ-GoLLIE-13B-AsSafeTensors.i1-IQ2_XS.gguf) | i1-IQ2_XS | 4.0 |  |
| [GGUF](https://huggingface.co/mradermacher/HiTZ-GoLLIE-13B-AsSafeTensors-i1-GGUF/resolve/main/HiTZ-GoLLIE-13B-AsSafeTensors.i1-IQ2_S.gguf) | i1-IQ2_S | 4.3 |  |
| [GGUF](https://huggingface.co/mradermacher/HiTZ-GoLLIE-13B-AsSafeTensors-i1-GGUF/resolve/main/HiTZ-GoLLIE-13B-AsSafeTensors.i1-Q2_K_S.gguf) | i1-Q2_K_S | 4.5 | very low quality |
| [GGUF](https://huggingface.co/mradermacher/HiTZ-GoLLIE-13B-AsSafeTensors-i1-GGUF/resolve/main/HiTZ-GoLLIE-13B-AsSafeTensors.i1-IQ2_M.gguf) | i1-IQ2_M | 4.6 |  |
| [GGUF](https://huggingface.co/mradermacher/HiTZ-GoLLIE-13B-AsSafeTensors-i1-GGUF/resolve/main/HiTZ-GoLLIE-13B-AsSafeTensors.i1-Q2_K.gguf) | i1-Q2_K | 5.0 | IQ3_XXS probably better |
| [GGUF](https://huggingface.co/mradermacher/HiTZ-GoLLIE-13B-AsSafeTensors-i1-GGUF/resolve/main/HiTZ-GoLLIE-13B-AsSafeTensors.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 5.1 | lower quality |
| [GGUF](https://huggingface.co/mradermacher/HiTZ-GoLLIE-13B-AsSafeTensors-i1-GGUF/resolve/main/HiTZ-GoLLIE-13B-AsSafeTensors.i1-IQ3_XS.gguf) | i1-IQ3_XS | 5.5 |  |
| [GGUF](https://huggingface.co/mradermacher/HiTZ-GoLLIE-13B-AsSafeTensors-i1-GGUF/resolve/main/HiTZ-GoLLIE-13B-AsSafeTensors.i1-IQ3_S.gguf) | i1-IQ3_S | 5.8 | beats Q3_K* |
| [GGUF](https://huggingface.co/mradermacher/HiTZ-GoLLIE-13B-AsSafeTensors-i1-GGUF/resolve/main/HiTZ-GoLLIE-13B-AsSafeTensors.i1-Q3_K_S.gguf) | i1-Q3_K_S | 5.8 | IQ3_XS probably better |
| [GGUF](https://huggingface.co/mradermacher/HiTZ-GoLLIE-13B-AsSafeTensors-i1-GGUF/resolve/main/HiTZ-GoLLIE-13B-AsSafeTensors.i1-IQ3_M.gguf) | i1-IQ3_M | 6.1 |  |
| [GGUF](https://huggingface.co/mradermacher/HiTZ-GoLLIE-13B-AsSafeTensors-i1-GGUF/resolve/main/HiTZ-GoLLIE-13B-AsSafeTensors.i1-Q3_K_M.gguf) | i1-Q3_K_M | 6.4 | IQ3_S probably better |
| [GGUF](https://huggingface.co/mradermacher/HiTZ-GoLLIE-13B-AsSafeTensors-i1-GGUF/resolve/main/HiTZ-GoLLIE-13B-AsSafeTensors.i1-Q3_K_L.gguf) | i1-Q3_K_L | 7.0 | IQ3_M probably better |
| [GGUF](https://huggingface.co/mradermacher/HiTZ-GoLLIE-13B-AsSafeTensors-i1-GGUF/resolve/main/HiTZ-GoLLIE-13B-AsSafeTensors.i1-IQ4_XS.gguf) | i1-IQ4_XS | 7.1 |  |
| [GGUF](https://huggingface.co/mradermacher/HiTZ-GoLLIE-13B-AsSafeTensors-i1-GGUF/resolve/main/HiTZ-GoLLIE-13B-AsSafeTensors.i1-IQ4_NL.gguf) | i1-IQ4_NL | 7.5 | prefer IQ4_XS |
| [GGUF](https://huggingface.co/mradermacher/HiTZ-GoLLIE-13B-AsSafeTensors-i1-GGUF/resolve/main/HiTZ-GoLLIE-13B-AsSafeTensors.i1-Q4_0.gguf) | i1-Q4_0 | 7.5 | fast, low quality |
| [GGUF](https://huggingface.co/mradermacher/HiTZ-GoLLIE-13B-AsSafeTensors-i1-GGUF/resolve/main/HiTZ-GoLLIE-13B-AsSafeTensors.i1-Q4_K_S.gguf) | i1-Q4_K_S | 7.5 | optimal size/speed/quality |
| [GGUF](https://huggingface.co/mradermacher/HiTZ-GoLLIE-13B-AsSafeTensors-i1-GGUF/resolve/main/HiTZ-GoLLIE-13B-AsSafeTensors.i1-Q4_K_M.gguf) | i1-Q4_K_M | 8.0 | fast, recommended |
| [GGUF](https://huggingface.co/mradermacher/HiTZ-GoLLIE-13B-AsSafeTensors-i1-GGUF/resolve/main/HiTZ-GoLLIE-13B-AsSafeTensors.i1-Q4_1.gguf) | i1-Q4_1 | 8.3 |  |
| [GGUF](https://huggingface.co/mradermacher/HiTZ-GoLLIE-13B-AsSafeTensors-i1-GGUF/resolve/main/HiTZ-GoLLIE-13B-AsSafeTensors.i1-Q5_K_S.gguf) | i1-Q5_K_S | 9.1 |  |
| [GGUF](https://huggingface.co/mradermacher/HiTZ-GoLLIE-13B-AsSafeTensors-i1-GGUF/resolve/main/HiTZ-GoLLIE-13B-AsSafeTensors.i1-Q5_K_M.gguf) | i1-Q5_K_M | 9.3 |  |
| [GGUF](https://huggingface.co/mradermacher/HiTZ-GoLLIE-13B-AsSafeTensors-i1-GGUF/resolve/main/HiTZ-GoLLIE-13B-AsSafeTensors.i1-Q6_K.gguf) | i1-Q6_K | 10.8 | 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. Additional thanks to [@nicoboss](https://huggingface.co/nicoboss) for giving me access to his private supercomputer, enabling me to provide many more imatrix quants, at much higher quality, than I would otherwise be able to.

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