Luca-MN-iMat-GGUF / README.md
InferenceIllusionist's picture
Update README.md
3bf51b8 verified
|
raw
history blame
2 kB
---
license: apache-2.0
base_model_relation: quantized
quantized_by: Quant-Cartel
base_model: rAIfle/Luca-MN-bf16
pipeline_tag: text-generation
tags:
- iMat
- GGUF
- unsloth
- trl
- sft
---
```
e88 88e d8
d888 888b 8888 8888 ,"Y88b 888 8e d88
C8888 8888D 8888 8888 "8" 888 888 88b d88888
Y888 888P Y888 888P ,ee 888 888 888 888
"88 88" "88 88" "88 888 888 888 888
b
8b,
e88'Y88 d8 888
d888 'Y ,"Y88b 888,8, d88 ,e e, 888
C8888 "8" 888 888 " d88888 d88 88b 888
Y888 ,d ,ee 888 888 888 888 , 888
"88,d88 "88 888 888 888 "YeeP" 888
PROUDLY PRESENTS
```
# Luca-MN-iMat-GGUF
Quantized with love from fp32.
* Importance Matrix calculated using [groups_merged.txt](https://github.com/ggerganov/llama.cpp/discussions/5263#discussioncomment-8395384)
* 92 chunks
* n_ctx=512
* Importance Matrix uses fp32 precision model weights, fp32.imatrix file to be added in repo
Original model README [here](https://huggingface.co/rAIFle/Luca-MN-bf16) and below:
![image/png](https://cdn-uploads.huggingface.co/production/uploads/6569a4ed2419be6072890cf8/T_ITjuaHakgamjwuElcAs.png)
## Luca-MN-iMat-GGUF
This thing was just intended as an experiment but it turned out quite good. I had it both name and prompt imagegen for itself.
Created by running a high-r LoRA-pass over Nemo-Base with 2 epochs of some RP data, then a low-r pass with 0.5 epochs of the c2-data, then 3 epochs of DPO using [jondurbin/gutenberg-dpo-v0.1](https://huggingface.co/datasets/jondurbin/gutenberg-dpo-v0.1).
## Prompting
Use the `Mistral V3-Tekken` context- and instruct-templates. Temperature at about `1.25` seems to be the sweet spot, with either MinP at `0.05` or TopP at `0.9`. DRY/Smoothing etc depending on your preference.