Text Generation
Transformers
Safetensors
qwen2
mergekit
Merge
conversational
text-generation-inference
Instructions to use KaraKaraWarehouse/Matsutei-Qwen2.5-72b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KaraKaraWarehouse/Matsutei-Qwen2.5-72b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="KaraKaraWarehouse/Matsutei-Qwen2.5-72b") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("KaraKaraWarehouse/Matsutei-Qwen2.5-72b") model = AutoModelForCausalLM.from_pretrained("KaraKaraWarehouse/Matsutei-Qwen2.5-72b", 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]:])) - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use KaraKaraWarehouse/Matsutei-Qwen2.5-72b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "KaraKaraWarehouse/Matsutei-Qwen2.5-72b" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "KaraKaraWarehouse/Matsutei-Qwen2.5-72b", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/KaraKaraWarehouse/Matsutei-Qwen2.5-72b
- SGLang
How to use KaraKaraWarehouse/Matsutei-Qwen2.5-72b 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 "KaraKaraWarehouse/Matsutei-Qwen2.5-72b" \ --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": "KaraKaraWarehouse/Matsutei-Qwen2.5-72b", "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 "KaraKaraWarehouse/Matsutei-Qwen2.5-72b" \ --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": "KaraKaraWarehouse/Matsutei-Qwen2.5-72b", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use KaraKaraWarehouse/Matsutei-Qwen2.5-72b with Docker Model Runner:
docker model run hf.co/KaraKaraWarehouse/Matsutei-Qwen2.5-72b
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README.md
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<a href="https://www.youtube.com/watch?v=Bv1u_e_91Ow"><img src="https://cdn-uploads.huggingface.co/production/uploads/633e85093a17ab61de8d9073/IPyNLo-Yd1X0Kw9Csn3dx.png" style="margin-left:auto;margin-right:auto"></a>
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SteyrCannon had a weird vibe issue when it comes to world book lore info. So I've been falling back to my EurobeatVARemix merge. This merge should address that inital issue but I think there's other quirks to this one.
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<a href="https://www.youtube.com/watch?v=Bv1u_e_91Ow"><img src="https://cdn-uploads.huggingface.co/production/uploads/633e85093a17ab61de8d9073/IPyNLo-Yd1X0Kw9Csn3dx.png" style="margin-left:auto;margin-right:auto"></a>
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SteyrCannon had a weird vibe issue when it comes to world book lore info (When starting from afresh, it might get confused when world info is injected due to double chat messages). So I've been falling back to my EurobeatVARemix merge. This merge should address that inital issue but I think there's other quirks to this one.
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## Quants & Hosts
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