rubenz-org/qwen2-5-0-5b-instruct-mlc

Qwen2.5 0.5B Instruct MLC-LLM

This is a quantized and optimized version of Qwen2.5 0.5B Instruct compiled with MLC-LLM for WebGPU deployment in browsers.

Model Details

• Base Model: Qwen2.5 0.5B Instruct
• Quantization: q4f32_1 (4-bit quantization with float32 scale)
• Context Window: 2048 tokens
• Prefill Chunk Size: 512 tokens
• Target: WebGPU deployment via WebLLM
• Memory Usage: ~800MB VRAM
• Total Parameters: 494,032,768
• Bits per Parameter: 5.004

Usage

With WebLLM

import * as webllm from '@mlc-ai/web-llm';

const customModels = [
  {
    model: "https://huggingface.co/rubenz-org/qwen2-5-0-5b-instruct-mlc",
    model_id: "qwen2.5-0.5b-instruct-custom",
    // Use official WebLLM WASM runtime for compatibility
    model_lib: "https://raw.githubusercontent.com/mlc-ai/binary-mlc-llm-libs/main/Qwen2.5-0.5B-Instruct-q4f32_1-MLC-1k.wasm",
    vram_required_MB: 800,
    low_resource_required: true,
    overrides: {
      context_window_size: 2048,
      prefill_chunk_size: 512,
    },
  },
];

const engine = await webllm.CreateMLCEngine("qwen2.5-0.5b-instruct-custom", {
  appConfig: { model_list: customModels }
});

Example Chat

const response = await engine.chat.completions.create({
  messages: [{ role: 'user', content: 'Hello! How can you help me today?' }],
  stream: true,
  temperature: 0.7,
  max_tokens: 512,
});

for await (const chunk of response) {
  const content = chunk.choices[0]?.delta?.content || '';
  if (content) {
    console.log(content);
  }
}

Files

• mlc-chat-config.json: Model configuration for MLC-LLM
• params_shard_*.bin: Quantized model parameters (8 shards)
• tokenizer.json, vocab.json, merges.txt: Tokenizer files
• tensor-cache.json: Parameter metadata cache
• Uses official WebLLM WASM runtime for compatibility

Performance

This model is optimized for browser deployment with:

• Reduced memory footprint through 4-bit quantization
• WebGPU acceleration for efficient inference
• Chunked prefill for better memory management
• Low resource requirements for edge deployment
• Compatible with official WebLLM runtime libraries

Browser Compatibility

• Chrome 113+ with WebGPU enabled
• Edge 113+ with WebGPU enabled
• Firefox with WebGPU experimental support

Memory Requirements

• Without KV cache: 629.45 MB
• With 4K KV cache: 725.45 MB
• Parameters: 294.70 MB
• Temporary buffer: 334.75 MB

License

This model follows the same license as the original Qwen2.5 model (Apache 2.0).