Instructions to use utter-project/EuroMoE-2.6B-A0.6B-2512 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use utter-project/EuroMoE-2.6B-A0.6B-2512 with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="utter-project/EuroMoE-2.6B-A0.6B-2512")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("utter-project/EuroMoE-2.6B-A0.6B-2512")
model = AutoModelForCausalLM.from_pretrained("utter-project/EuroMoE-2.6B-A0.6B-2512", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use utter-project/EuroMoE-2.6B-A0.6B-2512 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "utter-project/EuroMoE-2.6B-A0.6B-2512"
# 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/EuroMoE-2.6B-A0.6B-2512",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/utter-project/EuroMoE-2.6B-A0.6B-2512

SGLang

How to use utter-project/EuroMoE-2.6B-A0.6B-2512 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/EuroMoE-2.6B-A0.6B-2512" \
    --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/EuroMoE-2.6B-A0.6B-2512",
		"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/EuroMoE-2.6B-A0.6B-2512" \
        --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/EuroMoE-2.6B-A0.6B-2512",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use utter-project/EuroMoE-2.6B-A0.6B-2512 with Docker Model Runner:
```
docker model run hf.co/utter-project/EuroMoE-2.6B-A0.6B-2512
```

DuarteMRAlves commited on Feb 6

Commit

4efd074

verified ·

1 Parent(s): 2a1ff4b

Create README.md

Browse files

Files changed (1) hide show

README.md +54 -0

README.md ADDED Viewed

	@@ -0,0 +1,54 @@

+---
+license: apache-2.0
+language:
+- en
+- de
+- es
+- fr
+- it
+- pt
+- pl
+- nl
+- tr
+- sv
+- cs
+- el
+- hu
+- ro
+- fi
+- uk
+- sl
+- sk
+- da
+- lt
+- lv
+- et
+- bg
+- 'no'
+- ca
+- hr
+- ga
+- mt
+- gl
+- zh
+- ru
+- ko
+- ja
+- ar
+- hi
+library_name: transformers
+---
+# Model Card for EuroLLM-9B-2512
+This is the model card for EuroLLM-2.6B-A0.6-2512, the pre-trained model for [EuroLLM-2.6B-A0.6-2512-Instruct](https://huggingface.co/utter-project/EuroMoE-2.6B-A0.6B-Instruct-2512).
+- **Developed by:** Instituto Superior Técnico - University of Lisbon, Instituto de Telecomunicações, University of Edinburgh, Aveni, Unbabel, University of Paris-Saclay, Artefact Research Center, University of Amsterdam, Naver Labs, Sorbonne Université.
+- **Funded by:** European Union.
+- **Model type:** A 2.6B parameter multilingual transfomer LLM.
+- **Language(s) (NLP):** Bulgarian, Croatian, Czech, Danish, Dutch, English, Estonian, Finnish, French, German, Greek, Hungarian, Irish, Italian, Latvian, Lithuanian, Maltese, Polish, Portuguese, Romanian, Slovak, Slovenian, Spanish, Swedish, Arabic, Catalan, Chinese, Galician, Hindi, Japanese, Korean, Norwegian, Russian, Turkish, and Ukrainian.
+- **License:** Apache License 2.0.
+## Bias, Risks, and Limitations
+This model has not been aligned to human preferences, so the model may generate problematic outputs (e.g., hallucinations, harmful content, or false statements).