edoproch / deepseekr1-distilled-llama-70b-ollama

DeepSeek-R1 distilled on LLaMA3.3 70B and quantized by ollama

Cold

Public
17 runs
A100 (80GB)
Weights
Paper
License

Run with an API

Playground API Examples README Versions

Prediction

edoproch/deepseekr1-distilled-llama-70b-ollama:492f5241

Model

edoproch/deepseekr1-distilled-llama-70b-ollama:492f5241

qnaskaran9rj60cmq1ss93awb0

Status

Succeeded

Source

Web

Hardware

A100 (80GB)

Total duration

4m 58s

Created

about 1 month ago

Input

prompt: Solve x+3=5
temperature: 0.6

{
  "prompt": "Solve x+3=5",
  "temperature": 0.6
}

Install Replicate’s Node.js client library

npm 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 and set up the client

import Replicate from "replicate";

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

Run edoproch/deepseekr1-distilled-llama-70b-ollama using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "edoproch/deepseekr1-distilled-llama-70b-ollama:492f524178141b96d3039889672dfca9cacf78d4bfe096e5d3523963fdc7efe7",
  {
    input: {
      prompt: "Solve x+3=5",
      temperature: 0.6
    }
  }
);
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

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 edoproch/deepseekr1-distilled-llama-70b-ollama using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "edoproch/deepseekr1-distilled-llama-70b-ollama:492f524178141b96d3039889672dfca9cacf78d4bfe096e5d3523963fdc7efe7",
    input={
        "prompt": "Solve x+3=5",
        "temperature": 0.6
    }
)

# The edoproch/deepseekr1-distilled-llama-70b-ollama 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/edoproch/deepseekr1-distilled-llama-70b-ollama/api#output-schema
    print(item, end="")

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

Set the REPLICATE_API_TOKEN environment variable

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Run edoproch/deepseekr1-distilled-llama-70b-ollama 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": "492f524178141b96d3039889672dfca9cacf78d4bfe096e5d3523963fdc7efe7",
    "input": {
      "prompt": "Solve x+3=5",
      "temperature": 0.6
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Install Cog

brew install cog

If you don’t have Homebrew, there are other installation options available.

Pull and run edoproch/deepseekr1-distilled-llama-70b-ollama using Cog (this will download the full model and run it in your local environment):

cog predict r8.im/edoproch/deepseekr1-distilled-llama-70b-ollama@sha256:492f524178141b96d3039889672dfca9cacf78d4bfe096e5d3523963fdc7efe7 \
  -i 'prompt="Solve x+3=5"' \
  -i 'temperature=0.6'

To learn more, take a look at the Cog documentation.

Pull and run edoproch/deepseekr1-distilled-llama-70b-ollama using Docker (this will download the full model and run it in your local environment):

docker run -d -p 5000:5000 --gpus=all r8.im/edoproch/deepseekr1-distilled-llama-70b-ollama@sha256:492f524178141b96d3039889672dfca9cacf78d4bfe096e5d3523963fdc7efe7
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "prompt": "Solve x+3=5",
      "temperature": 0.6
    }
  }' \
  http://localhost:5000/predictions

Output

<think> I need to solve the equation \( x + 3 = 5 \). First, I'll isolate the variable by subtracting 3 from both sides of the equation. This will give me the value of \( x \). </think> To solve the equation \( x + 3 = 5 \), follow these steps: 1. **Subtract 3 from both sides** to isolate the variable \( x \): \[ x + 3 - 3 = 5 - 3 \] 2. **Simplify** both sides: \[ x = 2 \] Therefore, the solution is: \[ x = \boxed{2} \]

{
  "completed_at": "2025-01-30T18:27:13.065517Z",
  "created_at": "2025-01-30T18:22:14.698000Z",
  "data_removed": false,
  "error": null,
  "id": "qnaskaran9rj60cmq1ss93awb0",
  "input": {
    "prompt": "Solve x+3=5",
    "temperature": 0.6
  },
  "logs": null,
  "metrics": {
    "predict_time": 16.364897082,
    "total_time": 298.367517
  },
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  ],
  "started_at": "2025-01-30T18:26:56.700620Z",
  "status": "succeeded",
  "urls": {
    "stream": "https://stream-g.svc.rno2.c.replicate.net/v1/streams/6w523x33yc6vl7t3qxbgeeb7vo5kmvybddnq4es645q2sw33ihyq",
    "get": "https://api.replicate.com/v1/predictions/qnaskaran9rj60cmq1ss93awb0",
    "cancel": "https://api.replicate.com/v1/predictions/qnaskaran9rj60cmq1ss93awb0/cancel"
  },
  "version": "492f524178141b96d3039889672dfca9cacf78d4bfe096e5d3523963fdc7efe7"
}

Generated in

16.4 seconds

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