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continuum-ai
/
qwen2.5-coder-7b-compacted

Text Generation
MLX
Safetensors
Rust
qwen2
7b
agentic-coding
android
apple-silicon
attested
bash
c
chain-of-custody
chinese
code
code-completion
code-generation
code-infill
compacted
compensation-lora
consumer-gpu
cpp
cryptographically-verified
css
distillation
edge-inference
efficient
embedded
english
forge-alloy
function-calling
general
general-purpose
go
head-pruning
html
iphone
java
javascript
knowledge-distillation
kotlin
llama-cpp
lm-studio
local-inference
lora
macbook
mobile
multilingual
ollama
on-device
optimized
php
pruned
python
qwen
qwen-coder
qwen2.5
qwen2.5-coder
raspberry-pi
reproducible
ruby
sql
swift
teacher-student
typescript
validation-artifact
versatile
conversational
Model card Files Files and versions
xet
Community

Instructions to use continuum-ai/qwen2.5-coder-7b-compacted with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • MLX

    How to use continuum-ai/qwen2.5-coder-7b-compacted with MLX:

    # Make sure mlx-lm is installed
    # pip install --upgrade mlx-lm
    
    # Generate text with mlx-lm
    from mlx_lm import load, generate
    
    model, tokenizer = load("continuum-ai/qwen2.5-coder-7b-compacted")
    
    prompt = "Write a story about Einstein"
    messages = [{"role": "user", "content": prompt}]
    prompt = tokenizer.apply_chat_template(
        messages, add_generation_prompt=True
    )
    
    text = generate(model, tokenizer, prompt=prompt, verbose=True)
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • LM Studio
  • Pi new

    How to use continuum-ai/qwen2.5-coder-7b-compacted with Pi:

    Start the MLX server
    # Install MLX LM:
    uv tool install mlx-lm
    # Start a local OpenAI-compatible server:
    mlx_lm.server --model "continuum-ai/qwen2.5-coder-7b-compacted"
    Configure the model in Pi
    # Install Pi:
    npm install -g @mariozechner/pi-coding-agent
    # Add to ~/.pi/agent/models.json:
    {
      "providers": {
        "mlx-lm": {
          "baseUrl": "http://localhost:8080/v1",
          "api": "openai-completions",
          "apiKey": "none",
          "models": [
            {
              "id": "continuum-ai/qwen2.5-coder-7b-compacted"
            }
          ]
        }
      }
    }
    Run Pi
    # Start Pi in your project directory:
    pi
  • Hermes Agent new

    How to use continuum-ai/qwen2.5-coder-7b-compacted with Hermes Agent:

    Start the MLX server
    # Install MLX LM:
    uv tool install mlx-lm
    # Start a local OpenAI-compatible server:
    mlx_lm.server --model "continuum-ai/qwen2.5-coder-7b-compacted"
    Configure Hermes
    # Install Hermes:
    curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
    hermes setup
    # Point Hermes at the local server:
    hermes config set model.provider custom
    hermes config set model.base_url http://127.0.0.1:8080/v1
    hermes config set model.default continuum-ai/qwen2.5-coder-7b-compacted
    Run Hermes
    hermes
  • MLX LM

    How to use continuum-ai/qwen2.5-coder-7b-compacted with MLX LM:

    Generate or start a chat session
    # Install MLX LM
    uv tool install mlx-lm
    # Interactive chat REPL
    mlx_lm.chat --model "continuum-ai/qwen2.5-coder-7b-compacted"
    Run an OpenAI-compatible server
    # Install MLX LM
    uv tool install mlx-lm
    # Start the server
    mlx_lm.server --model "continuum-ai/qwen2.5-coder-7b-compacted"
    # Calling the OpenAI-compatible server with curl
    curl -X POST "http://localhost:8000/v1/chat/completions" \
       -H "Content-Type: application/json" \
       --data '{
         "model": "continuum-ai/qwen2.5-coder-7b-compacted",
         "messages": [
           {"role": "user", "content": "Hello"}
         ]
       }'
qwen2.5-coder-7b-compacted / eval
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  • 1 contributor
History: 2 commits
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EnricoFermi
Upload eval/humaneval/humaneval_samples.jsonl with huggingface_hub
c786f9f verified about 2 months ago
  • humaneval
    Upload eval/humaneval/humaneval_samples.jsonl with huggingface_hub about 2 months ago
  • calibrated_eval_results.json
    583 Bytes
    Upload eval/calibrated_eval_results.json with huggingface_hub about 2 months ago