Instructions to use MarinaraSpaghetti/NemoMix-Unleashed-12B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use MarinaraSpaghetti/NemoMix-Unleashed-12B with Transformers:

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

pipe = pipeline("text-generation", model="MarinaraSpaghetti/NemoMix-Unleashed-12B")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("MarinaraSpaghetti/NemoMix-Unleashed-12B")
model = AutoModelForCausalLM.from_pretrained("MarinaraSpaghetti/NemoMix-Unleashed-12B")

Inference
Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use MarinaraSpaghetti/NemoMix-Unleashed-12B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "MarinaraSpaghetti/NemoMix-Unleashed-12B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "MarinaraSpaghetti/NemoMix-Unleashed-12B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/MarinaraSpaghetti/NemoMix-Unleashed-12B

SGLang

How to use MarinaraSpaghetti/NemoMix-Unleashed-12B 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 "MarinaraSpaghetti/NemoMix-Unleashed-12B" \
    --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": "MarinaraSpaghetti/NemoMix-Unleashed-12B",
		"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 "MarinaraSpaghetti/NemoMix-Unleashed-12B" \
        --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": "MarinaraSpaghetti/NemoMix-Unleashed-12B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use MarinaraSpaghetti/NemoMix-Unleashed-12B with Docker Model Runner:
```
docker model run hf.co/MarinaraSpaghetti/NemoMix-Unleashed-12B
```

Is this good?

by Noxi-V - opened Nov 5, 2024

Discussion

Noxi-V

Nov 5, 2024

•

edited Nov 5, 2024

I know this might me a weird place to ask but I have seen the downloads being around 40k with only this and bart's gguf ones combined, I tried it before and it was decent...
Until it doesn't, it kept acting as me no matter what and I couldn't do anything to it forgetting things, yes I used the recommended settings and I play in usually 30k context size
Is it incompatible with that much context? (I guessed it can handle 30k since it's a nemo mix after all and from using llm explorer, it did say this model also supported to like 128k context)

MarinaraSpaghetti

Owner Nov 5, 2024

I know this might me a weird place to ask but I have seen the downloads being around 40k with only this and bart's gguf ones combined, I tried it before and it was decent...
Until it doesn't, it kept acting as me no matter what and I couldn't do anything to it forgetting things, yes I used the recommended settings and I play in usually 30k context size
Is it incompatible with that much context? (I guessed it can handle 30k since it's a nemo mix after all and from using llm explorer, it did say this model also supported to like 128k context)

What quant are you using (q4+ recommended), are you caching context in any way (don't), what are you using as a backend for the model (Oobabooga's WebUI recommended), is the instruct format correct for sure (it might have imported incorrectly due to ST's recently changed format)? If you want help, share some details first, please.

You can check opinions on how the model works here: https://huggingface.co/MarinaraSpaghetti/NemoMix-Unleashed-12B/discussions/1

I used it with 64k context on the q8_0 GGUF, and it was working fine, sometimes forgetful, but that's the magic of LLMs and perplexity. Never played for me, though.

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