EuroLLM-9B is a 9B parameter model trained on 4 trillion tokens divided across the considered languages and several data sources: Web data, parallel data (en-xx and xx-en), and high-quality datasets. For access, please fill out this form: https://forms.gle/kgvmkr6ucHN3xNuH6
Provider: All UTTER Project models | Cloudflare Workers AI
https://api.cloudflare.com/client/v4/accounts/{account_id}/ai/v1/chat/completionsInstall: pip install openai
import os
from openai import OpenAI
account_id = os.environ["CLOUDFLARE_ACCOUNT_ID"]
client = OpenAI(
api_key=os.environ["CLOUDFLARE_API_TOKEN"],
base_url=f"https://api.cloudflare.com/client/v4/accounts/{account_id}/ai/v1",
)
response = client.chat.completions.create(
model="@cf/utter-project/eurollm-9b-it",
messages=[
{"role": "user", "content": "Hello, how are you?"},
],
max_tokens=1024,
)
print(response.choices[0].message.content)Additional examples: Basic invoke, REST API (any task)
| Parameter | Type | Description |
|---|---|---|
| max_tokens | integer | Maximum tokens to generate. (≥1) |
| temperature | float | Controls randomness. Supported range varies by model. (≥0) |
| stream | boolean | Stream response chunks as they are generated. Default: false. |
Call text generation and embedding models with OpenAI-compatible client libraries using the account-scoped Workers AI base URL.
Run any Workers AI model, including image, speech, and embedding models, through the account-scoped /ai/run endpoint.
List available models, tasks, and per-model properties with the Workers AI models search API.