Camel 5B
An instruction-following five billion parameter large language model.
Deploy Camel 5B behind an API endpoint in seconds.
Deploy modelExample usage
This code example shows how to invoke the model using the requests library in Python. The model has a couple of key inputs:
instruction: The input text sent to the model.max_new_tokens: Allows you to control the length of the output sequence.
The output of the model is a JSON object which has a key called completion that contains the generated text.
Input
1import requests
2import os
3
4# Replace the empty string with your model id below
5model_id = ""
6baseten_api_key = os.environ["BASETEN_API_KEY"]
7
8data = {
9 "instruction": "Write a story about a new revolutionary space technology",
10 "max_new_tokens": 512
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)
19
20# Print the output of the model
21print(res.json())JSON output
1{
2 "completion": "In a world where humans have colonized the moon, a brilliant scientist discovers a hidden chamber in the lunar crust that holds the key to unlocking the secrets of the universe. Together with a daring team of astronauts, they embark on a daring mission to explore the chamber and unlock its incredible potential. As they venture through the uncharted regions of the moon's surface, they encounter unexpected challenges and uncover a hidden world teeming with life. As the team races against time to return home and share their discovery with the world, they must confront the consequences of their actions and decide whether to embrace a new age of space exploration or return to the safety of Earth."
3}
