Instructions to use Statuo/NemoMix-v4.0-EXL2-6bpw with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Statuo/NemoMix-v4.0-EXL2-6bpw with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="Statuo/NemoMix-v4.0-EXL2-6bpw")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Statuo/NemoMix-v4.0-EXL2-6bpw")
model = AutoModelForCausalLM.from_pretrained("Statuo/NemoMix-v4.0-EXL2-6bpw")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use Statuo/NemoMix-v4.0-EXL2-6bpw with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Statuo/NemoMix-v4.0-EXL2-6bpw"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Statuo/NemoMix-v4.0-EXL2-6bpw",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/Statuo/NemoMix-v4.0-EXL2-6bpw

SGLang

How to use Statuo/NemoMix-v4.0-EXL2-6bpw with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "Statuo/NemoMix-v4.0-EXL2-6bpw" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Statuo/NemoMix-v4.0-EXL2-6bpw",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "Statuo/NemoMix-v4.0-EXL2-6bpw" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Statuo/NemoMix-v4.0-EXL2-6bpw",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use Statuo/NemoMix-v4.0-EXL2-6bpw with Docker Model Runner:
```
docker model run hf.co/Statuo/NemoMix-v4.0-EXL2-6bpw
```

Honestly wanted to wait to quant these. It felt like they were pumping out new versions of it like clockwork to the point where I was wondering if MarinaraSpaghetti was even sleeping. But since this seems to be a clear-cut winner on the board, here we go.

This is the 6bpw EXL2 version of NemoMix 4.0. You can find the Original Model here
You can find the 8bpw version here
You can find the 4bpw version here

The best one so far out of all the Nemomixes. Use this one.

Information

Description

My main goal is to merge the smartness of the base Instruct Nemo with the better prose from the different roleplaying fine-tunes. This one seems to be the best out of all, so far. All credits and thanks go to Intervitens, Mistralai, Invisietch, and NeverSleep for providing amazing models used in the merge.

Instruct

Mistral Instruct.

<s>[INST] {system} [/INST] {assistant}</s>[INST] {user} [/INST]

Settings

Lower Temperature of 0.35 recommended, although I had luck with Temperatures above one (1.0-1.2) if you crank up the Min P (0.01-0.1). Run with base DRY of 0.8/1.75/2/0 and you're good to go.

Presets

You can use my custom context/instruct/parameters presets for the model from here.

https://huggingface.co/MarinaraSpaghetti/SillyTavern-Settings/tree/main

GGUF

https://huggingface.co/MarinaraSpaghetti/Nemomix-v4.0-12B-GGUF

Other Versions

V1: https://huggingface.co/MarinaraSpaghetti/Nemomix-v1.0-12B

V2: https://huggingface.co/MarinaraSpaghetti/Nemomix-v2.0-12B

V3: https://huggingface.co/MarinaraSpaghetti/Nemomix-v3.0-12B

V4: https://huggingface.co/MarinaraSpaghetti/Nemomix-v4.0-12B

Nemomix-v0.4-12B

This is a merge of pre-trained language models created using mergekit.

Merge Details

Merge Method

This model was merged using the della_linear merge method using F:\mergekit\mistralaiMistral-Nemo-Base-2407 as a base.

Models Merged

The following models were included in the merge:

F:\mergekit\intervitens_mini-magnum-12b-v1.1
F:\mergekit\mistralaiMistral-Nemo-Instruct-2407
F:\mergekit\invisietch_Atlantis-v0.1-12B
F:\mergekit\NeverSleepHistorical_lumi-nemo-e2.0

Configuration

The following YAML configuration was used to produce this model:

models:
  - model: F:\mergekit\invisietch_Atlantis-v0.1-12B
    parameters:
      weight: 0.16
      density: 0.4
  - model: F:\mergekit\mistralaiMistral-Nemo-Instruct-2407
    parameters:
      weight: 0.23
      density: 0.5
  - model: F:\mergekit\NeverSleepHistorical_lumi-nemo-e2.0
    parameters:
      weight: 0.27
      density: 0.6
  - model: F:\mergekit\intervitens_mini-magnum-12b-v1.1
    parameters:
      weight: 0.34
      density: 0.8
merge_method: della_linear
base_model: F:\mergekit\mistralaiMistral-Nemo-Base-2407
parameters:
  epsilon: 0.05
  lambda: 1
  int8_mask: true
dtype: bfloat16

Ko-fi

Enjoying what I do? Consider donating here, thank you!

https://ko-fi.com/spicy_marinara

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