Instructions to use Epiculous/Crunchy-onion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Epiculous/Crunchy-onion with Transformers:

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

pipe = pipeline("text-generation", model="Epiculous/Crunchy-onion")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Epiculous/Crunchy-onion")
model = AutoModelForCausalLM.from_pretrained("Epiculous/Crunchy-onion", 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 Epiculous/Crunchy-onion with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/Epiculous/Crunchy-onion

SGLang

How to use Epiculous/Crunchy-onion 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 "Epiculous/Crunchy-onion" \
    --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": "Epiculous/Crunchy-onion",
		"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 "Epiculous/Crunchy-onion" \
        --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": "Epiculous/Crunchy-onion",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use Epiculous/Crunchy-onion with Docker Model Runner:
```
docker model run hf.co/Epiculous/Crunchy-onion
```

Thanks

by deleted - opened Mar 25, 2024

Discussion

deleted

Mar 25, 2024

Hello again! Just came to say thank you. I started the Goliath 120b and then fell in LLM, but Crunchy onion is my all time fav! I'm using only Claude Opus and Crunchy 6.0bpw nowadays. (jailbreak is so annoying to set up lol) eta 3 + epsilon 3 are really good for Crunchy. I feel like it has all the intelligence and sense of local!

Plus, I think these models are kinda cool. If you have a time, try them later ^_^
Envoid/BondBurger-8x7B
ParasiticRogue/Merged-Vicuna-RP-Stew-34B
Masterjp123/SnowyRP-V2-13B-L2_BetaTest

Epiculous

Owner Mar 25, 2024

Very cool! I am happy to hear that it works so well! I'll definitely give those models you sent a look at some point, thanks for sharing!

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