Meta logoLlama 3.1 70B Instruct

Updated state of the art midsize LLM from Meta

Deploy Llama 3.1 70B Instruct behind an API endpoint in seconds.

Deploy model

Example usage

Input
1import requests
2
3# Replace the empty string with your model id below
4model_id = ""
5baseten_api_key = os.environ["BASETEN_API_KEY"]
6
7data = {
8    "prompt": "What even is AGI?",
9    "stream": True,
10    "max_tokens": 1024
11}
12
13# Call model endpoint
14res = requests.post(
15    f"https://model-{model_id}.api.baseten.co/production/predict",
16    headers={"Authorization": f"Api-Key {baseten_api_key}"},
17    json=data,
18    stream=True
19)
20
21# Print the generated tokens as they get streamed
22for content in res.iter_content():
23    print(content.decode("utf-8"), end="", flush=True)
JSON output
1[
2    "arrrg",
3    "me hearty",
4    "I",
5    "be",
6    "doing",
7    "..."
8]

Deploy any model in just a few commands

Avoid getting tangled in complex deployment processes. Deploy best-in-class open-source models and take advantage of optimized serving for your own models.

$

truss init -- example stable-diffusion-2-1-base ./my-sd-truss

$

cd ./my-sd-truss

$

export BASETEN_API_KEY=MdNmOCXc.YBtEZD0WFOYKso2A6NEQkRqTe

$

truss push

INFO

Serializing Stable Diffusion 2.1 truss.

INFO

Making contact with Baseten 👋 👽

INFO

🚀 Uploading model to Baseten 🚀

Upload progress: 0% | | 0.00G/2.39G