technillogue / mistral-instruct-webrtc-triton

  • Public
  • 13 runs
  • L40S
Iterate in playground

Input

pip install replicate
Set the REPLICATE_API_TOKEN environment variable:
export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Import the client:
import replicate

Run technillogue/mistral-instruct-webrtc-triton using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "technillogue/mistral-instruct-webrtc-triton:69d3e23a7548431723ac296c3a1d18ae8d1d7406322d2232e5e5e9c91f6a5cc6",
    input={
        "top_k": 0,
        "top_p": 0,
        "temperature": 1,
        "system_prompt": "You are a very helpful, respectful and honest assistant.",
        "length_penalty": 1,
        "max_new_tokens": 250,
        "prompt_template": "<s>[INST] {system_prompt} {prompt} [/INST]",
        "presence_penalty": 0,
        "frequency_penalty": 0
    }
)

# The technillogue/mistral-instruct-webrtc-triton model can stream output as it's running.
# The predict method returns an iterator, and you can iterate over that output.
for item in output:
    # https://replicate.com/technillogue/mistral-instruct-webrtc-triton/api#output-schema
    print(item, end="")

To learn more, take a look at the guide on getting started with Python.

Output

No output yet! Press "Submit" to start a prediction.

Run time and cost

This model runs on Nvidia L40S GPU hardware. We don't yet have enough runs of this model to provide performance information.

Readme

This model doesn't have a readme.