Instructions to use agentlans/Llama3.1-LexiHermes-SuperStorm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use agentlans/Llama3.1-LexiHermes-SuperStorm with Transformers:

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

pipe = pipeline("text-generation", model="agentlans/Llama3.1-LexiHermes-SuperStorm")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("agentlans/Llama3.1-LexiHermes-SuperStorm")
model = AutoModelForCausalLM.from_pretrained("agentlans/Llama3.1-LexiHermes-SuperStorm")
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

vLLM

How to use agentlans/Llama3.1-LexiHermes-SuperStorm with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "agentlans/Llama3.1-LexiHermes-SuperStorm"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "agentlans/Llama3.1-LexiHermes-SuperStorm",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/agentlans/Llama3.1-LexiHermes-SuperStorm

SGLang

How to use agentlans/Llama3.1-LexiHermes-SuperStorm 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 "agentlans/Llama3.1-LexiHermes-SuperStorm" \
    --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": "agentlans/Llama3.1-LexiHermes-SuperStorm",
		"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 "agentlans/Llama3.1-LexiHermes-SuperStorm" \
        --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": "agentlans/Llama3.1-LexiHermes-SuperStorm",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use agentlans/Llama3.1-LexiHermes-SuperStorm with Docker Model Runner:
```
docker model run hf.co/agentlans/Llama3.1-LexiHermes-SuperStorm
```
Browse Quantizations to use this model in llama.cpp, Ollama, LM Studio, or any compatible app.

Llama3.1-LexiHermes-SuperStorm

A mix of four high-performing models using the new SCE merging technique. This model was created using mergekit.

Models Merged

Base model: mlabonne/Meta-Llama-3.1-8B-Instruct-abliterated

Features

Solid and consistent style even without finetuning
Abliterated to avoid outright request refusals
Suitable for roleplaying (possibly due to Hermes component)
Can replace Llama 3.1 8B Instruct for general tasks

Limitations

Function calling and other languages not tested
May struggle with math and logic like other language models
Potential for factual errors, especially in specialized fields
Not intended for public deployment without additional safeguards

Merge Configuration

The following YAML configuration was used:

models:
  - model: Hermes-3-Llama-3.1-8B
  - model: Llama-3.1-8B-Lexi-Uncensored-V2
  - model: Llama-3.1-SuperNova-Lite
  - model: Llama-3.1-Storm-8B
merge_method: sce
base_model: Meta-Llama-3.1-8B-Instruct-abliterated
parameters:
  select_topk: 1.5
dtype: bfloat16