Instructions to use mlx-community/FastContext-1.0-4B-SFT-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use mlx-community/FastContext-1.0-4B-SFT-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("mlx-community/FastContext-1.0-4B-SFT-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

How to use mlx-community/FastContext-1.0-4B-SFT-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 "mlx-community/FastContext-1.0-4B-SFT-4bit"

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": "mlx-community/FastContext-1.0-4B-SFT-4bit"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

OpenClaw new

How to use mlx-community/FastContext-1.0-4B-SFT-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 "mlx-community/FastContext-1.0-4B-SFT-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 "mlx-community/FastContext-1.0-4B-SFT-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"

MLX LM

How to use mlx-community/FastContext-1.0-4B-SFT-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 "mlx-community/FastContext-1.0-4B-SFT-4bit"

Run an OpenAI-compatible server

# Install MLX LM
uv tool install mlx-lm
# Start the server
mlx_lm.server --model "mlx-community/FastContext-1.0-4B-SFT-4bit"
# Calling the OpenAI-compatible server with curl
curl -X POST "http://localhost:8000/v1/chat/completions" \
   -H "Content-Type: application/json" \
   --data '{
     "model": "mlx-community/FastContext-1.0-4B-SFT-4bit",
     "messages": [
       {"role": "user", "content": "Hello"}
     ]
   }'

Hermes Agent

How to use mlx-community/FastContext-1.0-4B-SFT-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 "mlx-community/FastContext-1.0-4B-SFT-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 mlx-community/FastContext-1.0-4B-SFT-4bit

Run Hermes

hermes

FastContext-1.0-4B-SFT-4bit / README.md

manjunathshiva

Add FastContext-1.0-4B-SFT MLX 4-bit quant

65edc36 verified about 1 month ago

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	---
	language: en
	license: mit
	library_name: mlx
	base_model: ShaunGves/FastContext-1.0-4B-SFT
	tags:
	- mlx
	- code
	- agent
	- repository-exploration
	pipeline_tag: text-generation
	---

	# FastContext-1.0-4B-SFT — MLX 4-bit

	MLX 4-bit quantization (4.501 bits per weight, ~2.1 GB) of
	[ShaunGves/FastContext-1.0-4B-SFT](https://huggingface.co/ShaunGves/FastContext-1.0-4B-SFT), a surviving
	mirror of Microsoft's FastContext repository-exploration subagent
	([arXiv:2606.14066](https://arxiv.org/abs/2606.14066)), removed from the official listings on 2026-06-30.
	Base model: Qwen3-4B-Instruct-2507. Converted with mlx-lm 0.29.1 (default group size 64).

	FastContext is a small explorer model for coding agents: given a natural-language query about a repository,
	it explores with read-only tools (Read / Glob / Grep, called in parallel) and returns a compact
	`<final_answer>` block of `file:line-range` citations, keeping broad exploration out of the main agent's
	context window.

	## ⚠️ Quality note (tested)

	In end-to-end tests with the [fastcontext CLI](https://github.com/manjunathshiva/fastcontext) on an M4 Mac,
	this 4-bit quant showed noticeably degraded path grounding: it repeatedly assumed wrong repository root
	paths, failed to recover from tool errors, and hallucinated citations to nonexistent files — on the same
	queries the [8-bit quant](https://huggingface.co/mlx-community/FastContext-1.0-4B-SFT-8bit) answered
	accurately. It is published for memory-constrained setups and further experimentation;
	prefer the 8-bit quant (~4 GB) if your machine allows. Run with `temperature ≤ 0.6` and cap
	`max_tokens` (missed stop tokens otherwise generate for minutes).

	## Use with LM Studio

	Search for `FastContext-1.0-4B-SFT-4bit` in LM Studio (MLX runtime), or:

	```bash
	lms get mlx-community/FastContext-1.0-4B-SFT-4bit
	```

	## Use with mlx-lm

	```bash
	uv tool install "mlx-lm==0.29.1" --with "transformers<5" --with "mlx<0.31"
	mlx_lm.server --model mlx-community/FastContext-1.0-4B-SFT-4bit --port 8080
	```

	## Use with the fastcontext CLI

	Install from the [preserved mirror](https://github.com/manjunathshiva/fastcontext) (includes fixes for
	local OpenAI-compatible servers), then from the repo you want to explore:

	```bash
	export BASE_URL="http://localhost:8080/v1" # or http://localhost:1234/v1 for LM Studio
	export MODEL="mlx-community/FastContext-1.0-4B-SFT-4bit"
	export API_KEY="local"
	export TEMPERATURE=0.6
	export MAX_TOKENS=4000

	fastcontext -q "Where is the retry logic for failed API calls?" --citation
	```