Text Generation
MLX
Safetensors
GGUF
Rust
qwen3_5
27b
4bit
agentic-coding
alloy-backfilled
android
apple-silicon
attested
bash
c
chain-of-custody
chinese
code
code-completion
code-generation
code-infill
coder
coding
compacted
consumer-gpu
cpp
cryptographically-verified
css
derivative
edge-inference
efficient
embedded
english
forge-alloy
function-calling
ggml
go
head-pruning
html
iphone
java
javascript
kotlin
llama-cpp
lm-studio
local-inference
macbook
mlx-4bit
mobile
multilingual
ollama
on-device
optimized
php
programming
pruned
python
quantized
qwen
qwen3
qwen3.5
raspberry-pi
reproducible
ruby
software-engineering
sql
swift
typescript
conversational
8-bit precision
Instructions to use continuum-ai/qwen3.5-27b-code-forged-mlx-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use continuum-ai/qwen3.5-27b-code-forged-mlx-4bit 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/qwen3.5-27b-code-forged-mlx-4bit") 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 Settings
- LM Studio
- Pi
How to use continuum-ai/qwen3.5-27b-code-forged-mlx-4bit 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/qwen3.5-27b-code-forged-mlx-4bit"
Configure the model in Pi
# Install Pi: npm install -g @earendil-works/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/qwen3.5-27b-code-forged-mlx-4bit" } ] } } }Run Pi
# Start Pi in your project directory: pi
- MLX LM
How to use continuum-ai/qwen3.5-27b-code-forged-mlx-4bit 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/qwen3.5-27b-code-forged-mlx-4bit"
Run an OpenAI-compatible server
# Install MLX LM uv tool install mlx-lm # Start the server mlx_lm.server --model "continuum-ai/qwen3.5-27b-code-forged-mlx-4bit" # 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/qwen3.5-27b-code-forged-mlx-4bit", "messages": [ {"role": "user", "content": "Hello"} ] }' - Hermes Agent
How to use continuum-ai/qwen3.5-27b-code-forged-mlx-4bit 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/qwen3.5-27b-code-forged-mlx-4bit"
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/qwen3.5-27b-code-forged-mlx-4bit
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use continuum-ai/qwen3.5-27b-code-forged-mlx-4bit with OpenClaw:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "continuum-ai/qwen3.5-27b-code-forged-mlx-4bit"
Configure OpenClaw
# Install OpenClaw: npm install -g openclaw@latest # Register the local server and set it as the default model: openclaw onboard --non-interactive --mode local \ --auth-choice custom-api-key \ --custom-base-url http://127.0.0.1:8080/v1 \ --custom-model-id "continuum-ai/qwen3.5-27b-code-forged-mlx-4bit" \ --custom-provider-id mlx-lm \ --custom-compatibility openai \ --custom-text-input \ --accept-risk \ --skip-health
Run OpenClaw
openclaw agent --local --agent main --message "Hello from Hugging Face"
fix: use hf.co (CORS-open) in verify URLs
Browse files
README.md
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<b>Trust: self-attested</b> · 1 benchmark · 2 devices tested<br>
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<a href="https://github.com/CambrianTech/forge-alloy">ForgeAlloy</a> chain of custody · <a href="qwen3.5-27b-code-forged-mlx-4bit.alloy.json">Download alloy</a> · Merkle-chained
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## Chain of Custody
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Scan the QR or [verify online](https://cambriantech.github.io/forge-alloy/verify/#
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<a href="https://cambriantech.github.io/forge-alloy/verify/#hf.co/continuum-ai/qwen3.5-27b-code-forged-mlx-4bit/resolve/main/qwen3.5-27b-code-forged-mlx-4bit.alloy.json@6ca79c62b879cd4c">
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<a href="https://cambriantech.github.io/forge-alloy/verify/#hf.co/continuum-ai/qwen3.5-27b-code-forged-mlx-4bit/resolve/main/qwen3.5-27b-code-forged-mlx-4bit.alloy.json@6ca79c62b879cd4c"><b>Every claim on this card is verified</b></a><br>
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<b>Trust: self-attested</b> · 1 benchmark · 2 devices tested<br>
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<a href="https://github.com/CambrianTech/forge-alloy">ForgeAlloy</a> chain of custody · <a href="qwen3.5-27b-code-forged-mlx-4bit.alloy.json">Download alloy</a> · Merkle-chained
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## Chain of Custody
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Scan the QR or [verify online](https://cambriantech.github.io/forge-alloy/verify/#hf.co/continuum-ai/qwen3.5-27b-code-forged-mlx-4bit/resolve/main/qwen3.5-27b-code-forged-mlx-4bit.alloy.json@6ca79c62b879cd4c). Download the [alloy file](qwen3.5-27b-code-forged-mlx-4bit.alloy.json) to verify independently.
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