adirik / mamba-130m

Base version of Mamba 130M, a 130 million parameter state space language model

Cold

Public
146 runs
L40S
GitHub
Paper
License

Iterate in playground

Run with an API

Playground API Examples README Versions

Prediction

adirik/mamba-130m:d7fe29cf1ad11cbd2fc28b808a7a7b4fd1ff880c394eaef914e40b6da08934ce

Model

adirik/mamba-130m:d7fe29cf

frwuol3brbrmsn3qargptfgsqq

Status

Succeeded

Source

Web

Hardware

A40

Total duration

89.0s

Created

over 1 year ago

Input

top_k: 1
top_p: 1
prompt: How are you doing today?
max_length: 100
temperature: 1
repetition_penalty: 1.2

{
  "top_k": 1,
  "top_p": 1,
  "prompt": "How are you doing today?",
  "max_length": 100,
  "temperature": 1,
  "repetition_penalty": 1.2
}

Install Replicate’s Node.js client library:

npm install replicate

Import and set up the client:

import Replicate from "replicate";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run adirik/mamba-130m using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "adirik/mamba-130m:d7fe29cf1ad11cbd2fc28b808a7a7b4fd1ff880c394eaef914e40b6da08934ce",
  {
    input: {
      top_k: 1,
      top_p: 1,
      prompt: "How are you doing today?",
      max_length: 100,
      temperature: 1,
      repetition_penalty: 1.2
    }
  }
);

console.log(output);

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

Install Replicate’s Python client library:

pip install replicate

Import the client:

import replicate

Run adirik/mamba-130m using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "adirik/mamba-130m:d7fe29cf1ad11cbd2fc28b808a7a7b4fd1ff880c394eaef914e40b6da08934ce",
    input={
        "top_k": 1,
        "top_p": 1,
        "prompt": "How are you doing today?",
        "max_length": 100,
        "temperature": 1,
        "repetition_penalty": 1.2
    }
)

# The adirik/mamba-130m 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/adirik/mamba-130m/api#output-schema
    print(item, end="")

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

Run adirik/mamba-130m using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

curl -s -X POST \
  -H "Authorization: Bearer $REPLICATE_API_TOKEN" \
  -H "Content-Type: application/json" \
  -H "Prefer: wait" \
  -d $'{
    "version": "adirik/mamba-130m:d7fe29cf1ad11cbd2fc28b808a7a7b4fd1ff880c394eaef914e40b6da08934ce",
    "input": {
      "top_k": 1,
      "top_p": 1,
      "prompt": "How are you doing today?",
      "max_length": 100,
      "temperature": 1,
      "repetition_penalty": 1.2
    }
  }' \
  https://api.replicate.com/v1/predictions

To learn more, take a look at Replicate’s HTTP API reference docs.

Output

I'm just getting back from a trip to the beach. I've been working on my new book, and it's going really well! It was great seeing you guys again last week at our first meeting with your team in New York City (we're still in NYC). We had such an amazing time there that we decided not only did we want more of your work but also wanted some extra time for us as part-time writers so this is what happened: We were able get together

{
  "completed_at": "2024-02-05T18:28:15.852978Z",
  "created_at": "2024-02-05T18:26:46.837864Z",
  "data_removed": false,
  "error": null,
  "id": "frwuol3brbrmsn3qargptfgsqq",
  "input": {
    "top_k": 1,
    "top_p": 1,
    "prompt": "How are you doing today?",
    "max_length": 100,
    "temperature": 1,
    "repetition_penalty": 1.2
  },
  "logs": null,
  "metrics": {
    "predict_time": 5.45327,
    "total_time": 89.015114
  },
  "output": [
    "\n",
    "",
    "",
    "I'm ",
    "just ",
    "getting ",
    "back ",
    "from ",
    "a ",
    "trip ",
    "to ",
    "the ",
    "",
    "beach. ",
    "",
    "I've ",
    "been ",
    "working ",
    "on ",
    "my ",
    "new ",
    "",
    "book, ",
    "and ",
    "",
    "it's ",
    "going ",
    "really ",
    "",
    "well! ",
    "It ",
    "was ",
    "great ",
    "seeing ",
    "you ",
    "guys ",
    "again ",
    "last ",
    "week ",
    "at ",
    "our ",
    "first ",
    "meeting ",
    "with ",
    "your ",
    "team ",
    "in ",
    "New ",
    "York ",
    "City ",
    "",
    "",
    "(we're ",
    "still ",
    "in ",
    "",
    "NYC). ",
    "We ",
    "had ",
    "such ",
    "an ",
    "amazing ",
    "time ",
    "there ",
    "that ",
    "we ",
    "decided ",
    "not ",
    "only ",
    "did ",
    "we ",
    "want ",
    "more ",
    "of ",
    "your ",
    "work ",
    "but ",
    "also ",
    "wanted ",
    "some ",
    "extra ",
    "time ",
    "for ",
    "us ",
    "as ",
    "",
    "",
    "part-time ",
    "writers ",
    "so ",
    "this ",
    "is ",
    "what ",
    "",
    "happened:\n",
    "",
    "We ",
    "were ",
    "able ",
    "get ",
    "together"
  ],
  "started_at": "2024-02-05T18:28:10.399708Z",
  "status": "succeeded",
  "urls": {
    "stream": "https://streaming-api.svc.us.c.replicate.net/v1/streams/ai5dxuaxmovng3hxshmz6zw6n6kwn52da6jo7qumg5hot6oix4aa",
    "get": "https://api.replicate.com/v1/predictions/frwuol3brbrmsn3qargptfgsqq",
    "cancel": "https://api.replicate.com/v1/predictions/frwuol3brbrmsn3qargptfgsqq/cancel"
  },
  "version": "d7fe29cf1ad11cbd2fc28b808a7a7b4fd1ff880c394eaef914e40b6da08934ce"
}

Generated in

5.5 seconds

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