---
license: apache-2.0
tags:
- mistral
- conversational
- text-generation-inference
base_model: UsernameJustAnother/Nemo-12B-Marlin-v5
library_name: transformers
---

> [!WARNING]
> **General Use Sampling:**<br>
> Mistral-Nemo-12B is very sensitive to the temperature sampler, try values near **0.3** at first or else you will get some weird results. This is mentioned by MistralAI at their [Transformers](https://huggingface.co/mistralai/Mistral-Nemo-Instruct-2407#transformers) section.

> [!NOTE]
> **Best Samplers:**<br>
> I found best success using the following for Nemo-12B-Marlin-v5:<br>
> Temperature: `0.7`-`0.8`<br>
> Top K: `-1`<br>
> Min P: `0.05`<br>
> Rep Penalty: `1.03` (Note, it is recommended to increase this as context length increases, I find `1.10` to be good at 16k+ context)

Currently this is my favorite Mistral-Nemo finetune to be released.

**Original Model:** [UsernameJustAnother/Nemo-12B-Marlin-v5](https://huggingface.co/UsernameJustAnother/Nemo-12B-Marlin-v5) (Thank you so much for your work ♥)

**Official Quants:** [UsernameJustAnother/Nemo-12B-Marlin-v5-gguf ](https://huggingface.co/UsernameJustAnother/Nemo-12B-Marlin-v5-gguf) (Currently only `Q8_0`)

**How to Use:** [llama.cpp](https://github.com/ggerganov/llama.cpp)

**Original Model License:** Apache 2.0

**Release Used:** [b3538](https://github.com/ggerganov/llama.cpp/releases/tag/b3538)

# Quants
PPL = Perplexity, lower is better<br>
Comparisons are done as QX_X Llama-3-8B against FP16 Llama-3-8B, recommended as a guideline and not as fact.
| Quant Type | Note | Size |
| ---- | ---- | ---- |
| [Q2_K](https://huggingface.co/starble-dev/Nemo-12B-Marlin-v5-GGUF/blob/main/Nemo-12B-Marlin-v5-Q2_K.gguf) | +3.5199 ppl @ Llama-3-8B | 4.79 GB |
| [Q3_K_S](https://huggingface.co/starble-dev/Nemo-12B-Marlin-v5-GGUF/blob/main/Nemo-12B-Marlin-v5-Q3_K_S.gguf) | +1.6321 ppl @ Llama-3-8B | 5.53 GB |
| [Q3_K_M](https://huggingface.co/starble-dev/Nemo-12B-Marlin-v5-GGUF/blob/main/Nemo-12B-Marlin-v5-Q3_K_M.gguf) | +0.6569 ppl @ Llama-3-8B | 6.08 GB |
| [Q3_K_L](https://huggingface.co/starble-dev/Nemo-12B-Marlin-v5-GGUF/blob/main/Nemo-12B-Marlin-v5-Q3_K_L.gguf) | +0.5562 ppl @ Llama-3-8B | 6.56 GB |
| [Q4_K_S](https://huggingface.co/starble-dev/Nemo-12B-Marlin-v5-GGUF/blob/main/Nemo-12B-Marlin-v5-Q4_K_S.gguf) | +0.2689 ppl @ Llama-3-8B | 7.12 GB |
| [Q4_K_M](https://huggingface.co/starble-dev/Nemo-12B-Marlin-v5-GGUF/blob/main/Nemo-12B-Marlin-v5-Q4_K_M.gguf) | +0.1754 ppl @ Llama-3-8B | 7.48 GB |
| [Q5_K_S](https://huggingface.co/starble-dev/Nemo-12B-Marlin-v5-GGUF/blob/main/Nemo-12B-Marlin-v5-Q5_K_S.gguf) | +0.1049 ppl @ Llama-3-8B | 8.52 GB |
| [Q5_K_M](https://huggingface.co/starble-dev/Nemo-12B-Marlin-v5-GGUF/blob/main/Nemo-12B-Marlin-v5-Q5_K_M.gguf) | +0.0569 ppl @ Llama-3-8B | 8.73 GB |
| [Q6_K](https://huggingface.co/starble-dev/Nemo-12B-Marlin-v5-GGUF/blob/main/Nemo-12B-Marlin-v5-Q6_K.gguf) | +0.0217 ppl @ Llama-3-8B | 10.1 GB |
| [Q8_0](https://huggingface.co/starble-dev/Nemo-12B-Marlin-v5-GGUF/blob/main/Nemo-12B-Marlin-v5-Q8_0.gguf) | +0.0026 ppl @ Llama-3-8B | 13.00 GB |