Instructions to use utter-project/EuroLLM-1.7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use utter-project/EuroLLM-1.7B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="utter-project/EuroLLM-1.7B")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("utter-project/EuroLLM-1.7B") model = AutoModelForCausalLM.from_pretrained("utter-project/EuroLLM-1.7B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use utter-project/EuroLLM-1.7B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "utter-project/EuroLLM-1.7B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "utter-project/EuroLLM-1.7B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/utter-project/EuroLLM-1.7B
- SGLang
How to use utter-project/EuroLLM-1.7B 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 "utter-project/EuroLLM-1.7B" \ --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": "utter-project/EuroLLM-1.7B", "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 "utter-project/EuroLLM-1.7B" \ --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": "utter-project/EuroLLM-1.7B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use utter-project/EuroLLM-1.7B with Docker Model Runner:
docker model run hf.co/utter-project/EuroLLM-1.7B
Download tokenizer.model from utter-project/EuroLLM-1.7B: direct link, hf CLI and curl.
- Browser
- Download file 2.41 MB
-
https://huggingface.co/utter-project/EuroLLM-1.7B/resolve/refs%2Fpr%2F1/tokenizer.model
- Command line
-
hf download hf://utter-project/EuroLLM-1.7B@refs/pr/1/tokenizer.model
-
curl -L -o tokenizer.model https://huggingface.co/utter-project/EuroLLM-1.7B/resolve/refs%2Fpr%2F1/tokenizer.model
2.41 MB
- Xet hash:
- 3a151a4e1e52fc6f5144f999ababc71426ed8c53efc55d25ea37a51f9979aee0
- Size of remote file:
- 2.41 MB
- SHA256:
- 42957aec88804838805b335da1bbcce9d116024a20c6c4b56757648b9e348254
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