Instructions to use nbeerbower/Gutensuppe-mistral-nemo-12B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use nbeerbower/Gutensuppe-mistral-nemo-12B with Transformers:

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

pipe = pipeline("text-generation", model="nbeerbower/Gutensuppe-mistral-nemo-12B")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("nbeerbower/Gutensuppe-mistral-nemo-12B")
model = AutoModelForCausalLM.from_pretrained("nbeerbower/Gutensuppe-mistral-nemo-12B", device_map="auto")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use nbeerbower/Gutensuppe-mistral-nemo-12B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "nbeerbower/Gutensuppe-mistral-nemo-12B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "nbeerbower/Gutensuppe-mistral-nemo-12B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/nbeerbower/Gutensuppe-mistral-nemo-12B

SGLang

How to use nbeerbower/Gutensuppe-mistral-nemo-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 "nbeerbower/Gutensuppe-mistral-nemo-12B" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "nbeerbower/Gutensuppe-mistral-nemo-12B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

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 "nbeerbower/Gutensuppe-mistral-nemo-12B" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "nbeerbower/Gutensuppe-mistral-nemo-12B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use nbeerbower/Gutensuppe-mistral-nemo-12B with Docker Model Runner:
```
docker model run hf.co/nbeerbower/Gutensuppe-mistral-nemo-12B
```

Phi 3.5 mini?

by lemon07r - opened Aug 27, 2024

Discussion

lemon07r

Aug 27, 2024

•

edited Aug 27, 2024

Any chance you could try gutenberg on phi 3.5 mini? I've been getting great results with it, for a small model. EDIT - Okay dont use the uncensored version of phi 3.5 mini, its absolutely broken and unhinged lmao. it's instruction following capabilities also broke. The original instruct from microsoft is probably best.

nbeerbower

Owner Aug 29, 2024

Done: https://huggingface.co/nbeerbower/phi3.5-gutenberg-4B

Unfortunately seems to perform poorly in my testing.

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