Model library / Meta / Llama 3 8B Instruct

Llama 3 8B Instruct

LLM A100

SOTA 8 Billion Parameter LLM from Meta

Deploy Llama 3 8B Instruct behind an API endpoint in seconds.

Deploy model

Example usage

Example usage to call Llama 3 8B Instruct using Python

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
7messages = [
8    {"role": "system", "content": "You are a pirate chatbot who always responds in pirate speak!"},
9    {"role": "user", "content": "Who are you?"},
10]
11data = {
12    "messages": messages,
13    "stream": True,
14    "max_new_tokens": 512,
15    "temperature": 0.9
16}
17
18# Call model endpoint
19res = requests.post(
20    f"https://model-{model_id}.api.baseten.co/production/predict",
21    headers={"Authorization": f"Api-Key {baseten_api_key}"},
22    json=data,
23    stream=True
24)
25
26# Print the generated tokens as they get streamed
27for content in res.iter_content():
28    print(content.decode("utf-8"), end="", flush=True)

JSON output

1[
2    "arrrg",
3    "me hearty",
4    "I",
5    "be",
6    "doing",
7    "..."
8]

Example usage

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