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arcee-ai
/
SuperNova-Medius

Text Generation
Transformers
Safetensors
qwen2
mergekit
Merge
conversational
Eval Results (legacy)
text-generation-inference
Model card Files Files and versions
xet
Community
17

Instructions to use arcee-ai/SuperNova-Medius with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use arcee-ai/SuperNova-Medius with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-generation", model="arcee-ai/SuperNova-Medius")
    messages = [
        {"role": "user", "content": "Who are you?"},
    ]
    pipe(messages)
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForCausalLM
    
    tokenizer = AutoTokenizer.from_pretrained("arcee-ai/SuperNova-Medius")
    model = AutoModelForCausalLM.from_pretrained("arcee-ai/SuperNova-Medius")
    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]:]))
  • Inference
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps Settings
  • vLLM

    How to use arcee-ai/SuperNova-Medius with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "arcee-ai/SuperNova-Medius"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/chat/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "arcee-ai/SuperNova-Medius",
    		"messages": [
    			{
    				"role": "user",
    				"content": "What is the capital of France?"
    			}
    		]
    	}'
    Use Docker
    docker model run hf.co/arcee-ai/SuperNova-Medius
  • SGLang

    How to use arcee-ai/SuperNova-Medius 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 "arcee-ai/SuperNova-Medius" \
        --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": "arcee-ai/SuperNova-Medius",
    		"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 "arcee-ai/SuperNova-Medius" \
            --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": "arcee-ai/SuperNova-Medius",
    		"messages": [
    			{
    				"role": "user",
    				"content": "What is the capital of France?"
    			}
    		]
    	}'
  • Docker Model Runner

    How to use arcee-ai/SuperNova-Medius with Docker Model Runner:

    docker model run hf.co/arcee-ai/SuperNova-Medius
New discussion
Resources
  • PR & discussions documentation
  • Code of Conduct
  • Hub documentation

License compatibility

2
#17 opened 11 months ago by
Schilder

Improve language tag

#16 opened about 1 year ago by
lbourdois

Following the instructions

#15 opened over 1 year ago by
Markobes

This cross-architecture distillation, with Phi?

3
#14 opened over 1 year ago by
sometimesanotion

Template

1
#13 opened over 1 year ago by
isr431

Update SuperNova-Medius with a merge with Qwen/Qwen2.5-Coder-14B-Instruct + Further Training 😋

➕ 2
11
#12 opened over 1 year ago by
Joseph717171

max output tokens?

1
#11 opened over 1 year ago by
sirus

Is there any example tutorial on mergekit-tokensurgeon?

#10 opened over 1 year ago by
win10

We distilled the logits of Llama 3.1 405B using an offline approach.

#9 opened over 1 year ago by
sirus

Unusual tokenizer.json file size

#8 opened over 1 year ago by
AuriAetherwiing

How about a 3 way merge with a distillation from Mistral Large? :D

❤️ 1
#7 opened over 1 year ago by
DreamGenX

Ideal quantization levels

👍 1
2
#6 opened over 1 year ago by
jadbox

Multilingual, Uncensored and extensive vocabulary.

❤️ 5
5
#4 opened over 1 year ago by
Kukedlc

2 base models = a nice merge UI on the model page

2
#1 opened over 1 year ago by
victor
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