deepseek-ai / deepseek-coder-v2-lite-instruct

DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models in Code Intelligence

Cold

Public
427 runs
L40S
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Paper
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Prediction

deepseek-ai/deepseek-coder-v2-lite-instruct:a182159595ee209e25e673a5ab6f0293111dd6733df973f77efcd1f851123330

Model

deepseek-ai/deepseek-coder-v2-lite-instruct:a1821595

ha35gkakfdrgm0cgjf4rm0gfm8

Status

Succeeded

Source

Web

Hardware

A40 (Large)

Total duration

1.7s

Created

10 months ago

Input

top_k: 50
top_p: 0.9
prompt: write a quick sort algorithm in python.
max_tokens: 512
min_tokens: 0
temperature: 0.6
system_prompt: You are an expert software engineer proficient in multiple programming languages.
presence_penalty: 0
frequency_penalty: 0

{
  "top_k": 50,
  "top_p": 0.9,
  "prompt": "write a quick sort algorithm in python.",
  "max_tokens": 512,
  "min_tokens": 0,
  "temperature": 0.6,
  "system_prompt": "You are an expert software engineer proficient in multiple programming languages.",
  "presence_penalty": 0,
  "frequency_penalty": 0
}

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 deepseek-ai/deepseek-coder-v2-lite-instruct using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "deepseek-ai/deepseek-coder-v2-lite-instruct:a182159595ee209e25e673a5ab6f0293111dd6733df973f77efcd1f851123330",
  {
    input: {
      top_k: 50,
      top_p: 0.9,
      prompt: "write a quick sort algorithm in python.",
      max_tokens: 512,
      min_tokens: 0,
      temperature: 0.6,
      system_prompt: "You are an expert software engineer proficient in multiple programming languages.",
      presence_penalty: 0,
      frequency_penalty: 0
    }
  }
);

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 deepseek-ai/deepseek-coder-v2-lite-instruct using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "deepseek-ai/deepseek-coder-v2-lite-instruct:a182159595ee209e25e673a5ab6f0293111dd6733df973f77efcd1f851123330",
    input={
        "top_k": 50,
        "top_p": 0.9,
        "prompt": "write a quick sort algorithm in python.",
        "max_tokens": 512,
        "min_tokens": 0,
        "temperature": 0.6,
        "system_prompt": "You are an expert software engineer proficient in multiple programming languages.",
        "presence_penalty": 0,
        "frequency_penalty": 0
    }
)

# The deepseek-ai/deepseek-coder-v2-lite-instruct 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/deepseek-ai/deepseek-coder-v2-lite-instruct/api#output-schema
    print(item, end="")

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

Run deepseek-ai/deepseek-coder-v2-lite-instruct 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": "deepseek-ai/deepseek-coder-v2-lite-instruct:a182159595ee209e25e673a5ab6f0293111dd6733df973f77efcd1f851123330",
    "input": {
      "top_k": 50,
      "top_p": 0.9,
      "prompt": "write a quick sort algorithm in python.",
      "max_tokens": 512,
      "min_tokens": 0,
      "temperature": 0.6,
      "system_prompt": "You are an expert software engineer proficient in multiple programming languages.",
      "presence_penalty": 0,
      "frequency_penalty": 0
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

def quick_sort(arr): if len(arr) <= 1: return arr pivot = arr[len(arr) // 2] left = [x for x in arr if x < pivot] middle = [x for x in arr if x == pivot] right = [x for x in arr if x > pivot] return quick_sort(left) + middle + quick_sort(right) print(quick_sort([3,6,8,10,1,2,1]))

{
  "completed_at": "2024-07-08T19:19:24.930258Z",
  "created_at": "2024-07-08T19:19:23.259000Z",
  "data_removed": false,
  "error": null,
  "id": "ha35gkakfdrgm0cgjf4rm0gfm8",
  "input": {
    "top_k": 50,
    "top_p": 0.9,
    "prompt": "write a quick sort algorithm in python.",
    "max_tokens": 512,
    "min_tokens": 0,
    "temperature": 0.6,
    "system_prompt": "You are an expert software engineer proficient in multiple programming languages.",
    "presence_penalty": 0,
    "frequency_penalty": 0
  },
  "logs": "INFO 07-08 19:19:23 async_llm_engine.py:584] Received request 3bea0322126645299a822ea89c4e4778: prompt: 'write a quick sort algorithm in python.', params: SamplingParams(n=1, best_of=1, presence_penalty=0.0, frequency_penalty=0.0, repetition_penalty=1.0, temperature=0.6, top_p=0.9, top_k=50, min_p=0.0, seed=None, use_beam_search=False, length_penalty=1.0, early_stopping=False, stop=[], stop_token_ids=[100001], include_stop_str_in_output=False, ignore_eos=False, max_tokens=512, min_tokens=0, logprobs=None, prompt_logprobs=None, skip_special_tokens=True, spaces_between_special_tokens=True, truncate_prompt_tokens=None), prompt_token_ids: None, lora_request: None.\n stdoutINFO 07-08 19:19:23 metrics.py:341] Avg prompt throughput: 1.5 tokens/s, Avg generation throughput: 21.6 tokens/s, Running: 1 reqs, Swapped: 0 reqs, Pending: 0 reqs, GPU KV cache usage: 0.1%, CPU KV cache usage: 0.0%.\n stdoutGeneration took 1720466049.90sINFO 07-08 19:19:24 async_llm_engine.py:134] Finished request 3bea0322126645299a822ea89c4e4778.\n stdoutFormatted prompt: {system_prompt}\n\nUser: {prompt}\n\nAssistant:",
  "metrics": {
    "predict_time": 1.637787113,
    "total_time": 1.671258
  },
  "output": [
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    "\n",
    ""
  ],
  "started_at": "2024-07-08T19:19:23.292470Z",
  "status": "succeeded",
  "urls": {
    "stream": "https://streaming-api.svc.us.c.replicate.net/v1/streams/rp3y6oobige4rodjk2vl4uz5q5undz3tagqvqjwcph5jmlp7cyha",
    "get": "https://api.replicate.com/v1/predictions/ha35gkakfdrgm0cgjf4rm0gfm8",
    "cancel": "https://api.replicate.com/v1/predictions/ha35gkakfdrgm0cgjf4rm0gfm8/cancel"
  },
  "version": "a182159595ee209e25e673a5ab6f0293111dd6733df973f77efcd1f851123330"
}

Generated in

1.6 seconds

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