Instructions to use TildeAI/TildeOpen-30b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TildeAI/TildeOpen-30b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="TildeAI/TildeOpen-30b")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("TildeAI/TildeOpen-30b") model = AutoModelForCausalLM.from_pretrained("TildeAI/TildeOpen-30b") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use TildeAI/TildeOpen-30b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "TildeAI/TildeOpen-30b" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "TildeAI/TildeOpen-30b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/TildeAI/TildeOpen-30b
- SGLang
How to use TildeAI/TildeOpen-30b 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 "TildeAI/TildeOpen-30b" \ --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": "TildeAI/TildeOpen-30b", "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 "TildeAI/TildeOpen-30b" \ --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": "TildeAI/TildeOpen-30b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use TildeAI/TildeOpen-30b with Docker Model Runner:
docker model run hf.co/TildeAI/TildeOpen-30b
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**Developed by:** [Tilde.ai](https://tilde.ai/tildeopen-llm/)
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**Funded by:** European Commission via [EuroHPC JU Large AI Grand Challenge](https://www.eurohpc-ju.europa.eu/winners-announced-large-ai-grand-challenge-2024-06-26_en)
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**Model type:** A 30B parameter dense decoder-only transformer
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**Languages:** Albanian, Bosnian, Bulgarian, Croatian, Czech, Danish, Dutch, English, Estonian, Finnish, French, German, Hungarian, Icelandic, Irish, Italian, Latgalian, Latvian, Lithuanian, Macedonian, Maltese, Montenegrin, Norwegian, Polish, Portuguese, Romanian, Russian, Serbian, Slovak, Slovene, Spanish, Swedish, Turkish, Ukrainian as well
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**License:** CC-BY-4.0
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**Developed by:** [Tilde.ai](https://tilde.ai/tildeopen-llm/)
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**Funded by:** European Commission via [EuroHPC JU Large AI Grand Challenge](https://www.eurohpc-ju.europa.eu/winners-announced-large-ai-grand-challenge-2024-06-26_en)
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**Model type:** A 30B parameter dense decoder-only transformer
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**Languages:** Albanian, Bosnian, Bulgarian, Croatian, Czech, Danish, Dutch, English, Estonian, Finnish, French, German, Hungarian, Icelandic, Irish, Italian, Latgalian, Latvian, Lithuanian, Macedonian, Maltese, Montenegrin, Norwegian, Polish, Portuguese, Romanian, Russian, Serbian, Slovak, Slovene, Spanish, Swedish, Turkish, Ukrainian as well as mathematical proofs, programming code and XML documents containing translation data
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**License:** CC-BY-4.0
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