Instructions to use vitruv/vitruv_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vitruv/vitruv_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="vitruv/vitruv_2")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("vitruv/vitruv_2") model = AutoModelForCausalLM.from_pretrained("vitruv/vitruv_2") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use vitruv/vitruv_2 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "vitruv/vitruv_2" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "vitruv/vitruv_2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/vitruv/vitruv_2
- SGLang
How to use vitruv/vitruv_2 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 "vitruv/vitruv_2" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "vitruv/vitruv_2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'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 "vitruv/vitruv_2" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "vitruv/vitruv_2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use vitruv/vitruv_2 with Docker Model Runner:
docker model run hf.co/vitruv/vitruv_2
Update README.md
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README.md
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license: apache-2.0
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license: apache-2.0
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language:
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- ko
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---
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Who we are : Virtruv
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ν΄λΉ λͺ¨λΈμ νκ΅μ΄ μ€ μν λͺ¨λΈμ μ§μ€νμ¬ νμ΅μ μλνμμ΅λλ€.
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Base Model : 'vitruv/vitruv1'
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Dataset : 1 . traintogpb/aihub-koen-translation-integrated-tiny-100k
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kyujinpy/KOR-gugugu-platypus-set
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GAIR/MathPile : λ€μ λ°μ΄ν° μ
μ sampling νμ¬ μ§μ translate, νμμ΅λλ€.
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## What Added ?
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Dataset 3:
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μΆμ² : AIHUB
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DATASET 4: νκ΅μ΄ λ¬Έν (μν/λλΌλ§) λλ³Έ
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μΆμ² : AIHUB
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DATASET 5: μ λ¬Έ μ ν μλ΄ λ΄μ
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μΆμ² : AIHUB
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Prompt:
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