Instructions to use preparebuddy/ielts-3b-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use preparebuddy/ielts-3b-mlx 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("preparebuddy/ielts-3b-mlx") 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 preparebuddy/ielts-3b-mlx with Pi:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "preparebuddy/ielts-3b-mlx"
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": "preparebuddy/ielts-3b-mlx" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use preparebuddy/ielts-3b-mlx 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 "preparebuddy/ielts-3b-mlx"
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 preparebuddy/ielts-3b-mlx
Run Hermes
hermes
- MLX LM
How to use preparebuddy/ielts-3b-mlx with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Interactive chat REPL mlx_lm.chat --model "preparebuddy/ielts-3b-mlx"
Run an OpenAI-compatible server
# Install MLX LM uv tool install mlx-lm # Start the server mlx_lm.server --model "preparebuddy/ielts-3b-mlx" # Calling the OpenAI-compatible server with curl curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "preparebuddy/ielts-3b-mlx", "messages": [ {"role": "user", "content": "Hello"} ] }'
PrepareBuddy IELTS-3B — MLX build (Apple Silicon)
The MLX 8-bit build of PrepareBuddy IELTS-3B, for fast local use on Apple Silicon (Macs) — including LM Studio.
It generates IELTS Academic practice content across all four sections (Reading, Writing, Listening, Speaking). Full model details, examples, supported types, and limitations are on the main model page: 👉 https://huggingface.co/preparebuddy/ielts-3b
Content generator, not an assessment tool. A specialised fine-tune of SmolLM3-3B — not a from-scratch foundation model. Verdict answers (TFNG/YNNG) are ~70–75% accurate — review before use.
Tip: if LM Studio's MLX runtime gives a load error (a known LM Studio issue), use the GGUF build
preparebuddy/ielts-3b-ggufinstead — it loads via the rock-solidllama.cppruntime, on any OS.
Run it in LM Studio (Mac, Apple Silicon)
- In LM Studio, search
preparebuddy/ielts-3b-mlxand download it. - Load it, and in the system prompt paste:
You generate authentic IELTS Academic practice content across reading, writing, listening, and speaking. Produce passages, transcripts, tasks, questions, and answer keys or model answers as appropriate to the section. Use IELTS-style register: academic, neutral, factually plausible. This is content generation, not assessment.
- In the chat box, use the structured prompt, e.g.:
<TEST=IELTS><SECTION=READING><TYPE=TFNG><DIFF=medium><TOPIC=solar power> Generate a short passage with 4 True/False/Not Given statements and an answer key. - Settings: temperature 0.3 for verdict questions (TFNG/YNNG/MCQ), 0.7 for passages/writing/speaking; top_p 0.9.
Run it with mlx-lm (CLI)
pip install mlx-lm
python -m mlx_lm generate --model preparebuddy/ielts-3b-mlx \
--prompt "<TEST=IELTS><SECTION=WRITING><TYPE=TASK2><DIFF=medium><TOPIC=remote work> Generate an IELTS Academic Writing Task 2 question with word limit and timing." --temp 0.7
(Apply the chat template / system prompt for best results — see the main model page.)
License
Apache-2.0, inheriting from SmolLM3-3B. Built by PrepareBuddy.
- Downloads last month
- 30
8-bit
Model tree for preparebuddy/ielts-3b-mlx
Base model
HuggingFaceTB/SmolLM3-3B-Base