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---
base_model:
- 152334H/miqu-1-70b-sf
- lizpreciatior/lzlv_70b_fp16_hf
language:
- en
- de
- fr
- es
- it
library_name: transformers
tags:
- mergekit
- merge
---
# miquliz-120b
- EXL2: [2.4bpw](https://huggingface.co/LoneStriker/miquliz-120b-2.4bpw-h6-exl2) | [2.65bpw](https://huggingface.co/LoneStriker/miquliz-120b-2.65bpw-h6-exl2) | 2.9bpw | [4.0bpw](https://huggingface.co/LoneStriker/miquliz-120b-4.0bpw-h6-exl2)
- GGUF: [IQ3_XXS](https://huggingface.co/wolfram/miquliz-120b-GGUF) | [Q4_K_S+Q4_K_M](https://huggingface.co/NanoByte/miquliz-120b-Q4-GGUF)
- HF: [wolfram/miquliz-120b](https://huggingface.co/wolfram/miquliz-120b)
This is a 120b frankenmerge created by interleaving layers of [miqu-1-70b-sf](https://huggingface.co/152334H/miqu-1-70b-sf) with [lzlv_70b_fp16_hf](https://huggingface.co/lizpreciatior/lzlv_70b_fp16_hf) using [mergekit](https://github.com/cg123/mergekit).
Inspired by [goliath-120b](https://huggingface.co/alpindale/goliath-120b).
Thanks for the support, [CopilotKit](https://github.com/CopilotKit/CopilotKit) - the open-source platform for building in-app AI Copilots into any product, with any LLM model. Check out their GitHub.
Thanks for the EXL2 and GGUF quants, [Lone Striker](https://huggingface.co/LoneStriker) and [NanoByte](https://huggingface.co/NanoByte)!
## Prompt template: Mistral
```
<s>[INST] {prompt} [/INST]
```
See also: [🐺🐦⬛ LLM Prompt Format Comparison/Test: Mixtral 8x7B Instruct with **17** different instruct templates : LocalLLaMA](https://www.reddit.com/r/LocalLLaMA/comments/18ljvxb/llm_prompt_format_comparisontest_mixtral_8x7b/)
## Model Details
- Max Context: 32768 tokens
- Layers: 137
## Merge Details
### Merge Method
This model was merged using the passthrough merge method.
### Models Merged
The following models were included in the merge:
- [152334H/miqu-1-70b-sf](https://huggingface.co/152334H/miqu-1-70b-sf)
- [lizpreciatior/lzlv_70b_fp16_hf](https://huggingface.co/lizpreciatior/lzlv_70b_fp16_hf)
### Configuration
The following YAML configuration was used to produce this model:
```yaml
dtype: float16
merge_method: passthrough
slices:
- sources:
- layer_range: [0, 16]
model: 152334H/miqu-1-70b-sf
- sources:
- layer_range: [8, 24]
model: lizpreciatior/lzlv_70b_fp16_hf
- sources:
- layer_range: [17, 32]
model: 152334H/miqu-1-70b-sf
- sources:
- layer_range: [25, 40]
model: lizpreciatior/lzlv_70b_fp16_hf
- sources:
- layer_range: [33, 48]
model: 152334H/miqu-1-70b-sf
- sources:
- layer_range: [41, 56]
model: lizpreciatior/lzlv_70b_fp16_hf
- sources:
- layer_range: [49, 64]
model: 152334H/miqu-1-70b-sf
- sources:
- layer_range: [57, 72]
model: lizpreciatior/lzlv_70b_fp16_hf
- sources:
- layer_range: [65, 80]
model: 152334H/miqu-1-70b-sf
```
## Credits & Special Thanks
- 1st model:
- original (unreleased) model: [mistralai (Mistral AI_)](https://huggingface.co/mistralai)
- leaked model: [miqudev/miqu-1-70b](https://huggingface.co/miqudev/miqu-1-70b)
- f16 model: [152334H/miqu-1-70b-sf](https://huggingface.co/152334H/miqu-1-70b-sf)
- 2nd model: [lizpreciatior/lzlv_70b_fp16_hf](https://huggingface.co/lizpreciatior/lzlv_70b_fp16_hf)
- mergekit: [arcee-ai/mergekit: Tools for merging pretrained large language models.](https://github.com/arcee-ai/mergekit)
- mergekit_config.yml: [alpindale/goliath-120b](https://huggingface.co/alpindale/goliath-120b)
### Support
- [My Ko-fi page](https://ko-fi.com/wolframravenwolf) if you'd like to tip me to say thanks or request specific models to be tested or merged with priority. Also consider supporting your favorite model creators, quantizers, or frontend/backend devs if you can afford to do so. They deserve it!
#### DISCLAIMER: THIS IS [BASED ON A LEAKED ASSET](https://huggingface.co/miqudev/miqu-1-70b/discussions/10) AND HAS NO LICENSE ASSOCIATED WITH IT. USE AT YOUR OWN RISK.
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