lucataco / internlm2_5-7b-chat

InternLM2.5 has open-sourced a 7 billion parameter base model and a chat model tailored for practical scenarios.

Cold

Public
58 runs
L40S
Paper
License

Run with an API

Playground API Examples Train README Versions

Prediction

lucataco/internlm2_5-7b-chat:e943ac18ac8c05ac7deb01cbc3aba827b74f1ecdcb71d722e692d7ed4e70c33d

Model

lucataco/internlm2_5-7b-chat:e943ac18

hjke4jdzehrgj0cgfd684mexxg

Status

Succeeded

Source

Web

Hardware

A40 (Large)

Total duration

1m 54s

Created

11 months ago

Input

top_k: 50
top_p: 0.9
prompt: please provide three suggestions about time management
max_tokens: 512
min_tokens: 0
temperature: 0.6
system_prompt: You are a helpful assistant.
presence_penalty: 0
frequency_penalty: 0

{
  "top_k": 50,
  "top_p": 0.9,
  "prompt": "please provide three suggestions about time management",
  "max_tokens": 512,
  "min_tokens": 0,
  "temperature": 0.6,
  "system_prompt": "You are a helpful assistant.",
  "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 lucataco/internlm2_5-7b-chat using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "lucataco/internlm2_5-7b-chat:e943ac18ac8c05ac7deb01cbc3aba827b74f1ecdcb71d722e692d7ed4e70c33d",
  {
    input: {
      top_k: 50,
      top_p: 0.9,
      prompt: "please provide three suggestions about time management",
      max_tokens: 512,
      min_tokens: 0,
      temperature: 0.6,
      system_prompt: "You are a helpful assistant.",
      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 lucataco/internlm2_5-7b-chat using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "lucataco/internlm2_5-7b-chat:e943ac18ac8c05ac7deb01cbc3aba827b74f1ecdcb71d722e692d7ed4e70c33d",
    input={
        "top_k": 50,
        "top_p": 0.9,
        "prompt": "please provide three suggestions about time management",
        "max_tokens": 512,
        "min_tokens": 0,
        "temperature": 0.6,
        "system_prompt": "You are a helpful assistant.",
        "presence_penalty": 0,
        "frequency_penalty": 0
    }
)

# The lucataco/internlm2_5-7b-chat 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/lucataco/internlm2_5-7b-chat/api#output-schema
    print(item, end="")

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

Run lucataco/internlm2_5-7b-chat 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": "lucataco/internlm2_5-7b-chat:e943ac18ac8c05ac7deb01cbc3aba827b74f1ecdcb71d722e692d7ed4e70c33d",
    "input": {
      "top_k": 50,
      "top_p": 0.9,
      "prompt": "please provide three suggestions about time management",
      "max_tokens": 512,
      "min_tokens": 0,
      "temperature": 0.6,
      "system_prompt": "You are a helpful assistant.",
      "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

Certainly! Here are three suggestions for effective time management: 1. **Prioritize Tasks**: Start by identifying the most important tasks that need to be completed and prioritize them based on urgency and importance. Use tools like the Eisenhower Matrix to categorize tasks into four quadrants: urgent and important, important but not urgent, urgent but not important, and neither urgent nor important. Focus on completing tasks in the first quadrant first, as they contribute the most to your goals. 2. **Set Specific Goals**: Define clear, achievable goals for each day, week, and month. Break down larger projects into smaller, manageable tasks and set deadlines for each. This helps in maintaining focus and provides a sense of accomplishment as you complete each task. 3. **Use Time-Blocking**: Allocate specific blocks of time for different activities throughout your day. This involves scheduling tasks in your calendar, ensuring you dedicate time for work, breaks, and personal activities. Time-blocking helps in minimizing distractions and ensures that you have a structured approach to your day, maximizing productivity and reducing procrastination. Remember, effective time management is about balancing work with rest and leisure, so ensure you schedule time for relaxation and hobbies to maintain a healthy work-life balance.

{
  "completed_at": "2024-07-04T01:14:19.800970Z",
  "created_at": "2024-07-04T01:12:25.716000Z",
  "data_removed": false,
  "error": null,
  "id": "hjke4jdzehrgj0cgfd684mexxg",
  "input": {
    "top_k": 50,
    "top_p": 0.9,
    "prompt": "please provide three suggestions about time management",
    "max_tokens": 512,
    "min_tokens": 0,
    "temperature": 0.6,
    "system_prompt": "You are a helpful assistant.",
    "presence_penalty": 0,
    "frequency_penalty": 0
  },
  "logs": "INFO 07-04 01:14:12 async_llm_engine.py:529] Received request 6fffef91b60745a99f3323d98d0adf10: prompt: '<s><|im_start|>system\\nYou are a helpful assistant.<|im_end|>\\n<|im_start|>user\\nplease provide three suggestions about time management<|im_end|>\\n<|im_start|>assistant\\n', sampling_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=[2], 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 07-04 01:14:16 metrics.py:334] Avg prompt throughput: 5.8 tokens/s, Avg generation throughput: 29.3 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 1720054315.80sINFO 07-04 01:14:19 async_llm_engine.py:120] Finished request 6fffef91b60745a99f3323d98d0adf10.\n stdoutFormatted prompt: <s><|im_start|>system\nYou are a helpful assistant.<|im_end|>\n<|im_start|>user\nplease provide three suggestions about time management<|im_end|>\n<|im_start|>assistant",
  "metrics": {
    "predict_time": 6.915671904,
    "total_time": 114.08497
  },
  "output": [
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    "ertain",
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    ":\n\n",
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    " **",
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    " important",
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    " **",
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    ",",
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    ",",
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    " Time",
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    " helps",
    " in",
    " minim",
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    " distra",
    "ctions",
    " and",
    " ensures",
    " that",
    " you",
    " have",
    " a",
    " structured",
    " approach",
    " to",
    " your",
    " day",
    ",",
    " maxim",
    "izing",
    " productivity",
    " and",
    " reducing",
    " pro",
    "cr",
    "ast",
    "ination",
    ".\n\n",
    "Remember",
    ",",
    " effective",
    " time",
    " management",
    " is",
    " about",
    " balancing",
    " work",
    " with",
    " rest",
    " and",
    " leisure",
    ",",
    " so",
    " ensure",
    " you",
    " schedule",
    " time",
    " for",
    " relaxation",
    " and",
    " h",
    "obbies",
    " to",
    " maintain",
    " a",
    " healthy",
    " work",
    "-life",
    " balance",
    ".",
    ""
  ],
  "started_at": "2024-07-04T01:14:12.885298Z",
  "status": "succeeded",
  "urls": {
    "stream": "https://streaming-api.svc.us.c.replicate.net/v1/streams/ilhlpztibnz5dqxtqatu33vxp5sdkfmuqobxrdcezivkrmrvtoyq",
    "get": "https://api.replicate.com/v1/predictions/hjke4jdzehrgj0cgfd684mexxg",
    "cancel": "https://api.replicate.com/v1/predictions/hjke4jdzehrgj0cgfd684mexxg/cancel"
  },
  "version": "e943ac18ac8c05ac7deb01cbc3aba827b74f1ecdcb71d722e692d7ed4e70c33d"
}

Generated in

6.9 seconds

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