Instructions to use preparebuddy/ielts-3b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use preparebuddy/ielts-3b with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="preparebuddy/ielts-3b")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("preparebuddy/ielts-3b")
model = AutoModelForCausalLM.from_pretrained("preparebuddy/ielts-3b", device_map="auto")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use preparebuddy/ielts-3b with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "preparebuddy/ielts-3b"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "preparebuddy/ielts-3b",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/preparebuddy/ielts-3b

SGLang

How to use preparebuddy/ielts-3b with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "preparebuddy/ielts-3b" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "preparebuddy/ielts-3b",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "preparebuddy/ielts-3b" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "preparebuddy/ielts-3b",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use preparebuddy/ielts-3b with Docker Model Runner:
```
docker model run hf.co/preparebuddy/ielts-3b
```

preparebuddy commited on Jun 3

Commit

d2819e9

verified ·

1 Parent(s): 7d2e9c6

card: GGUF as primary local/LM Studio option

Browse files

Files changed (1) hide show

README.md +6 -4

README.md CHANGED Viewed

@@ -25,12 +25,14 @@ trained on PrepareBuddy's own curated IELTS content.
 Built by **PrepareBuddy**. A fine-tune of SmolLM3-3B — **not** a from-scratch foundation model.
-**Run it three ways:**
-- 🖥️ **Locally on a Mac (fast)** — the [MLX build](https://huggingface.co/preparebuddy/ielts-3b-mlx)
-  runs in **LM Studio** or `mlx-lm` on Apple Silicon.
 - 🐍 **In code** — `transformers` (this repo); see [Usage](#usage-transformers) below.
 - 🌐 **In your browser** — the [demo Space](https://huggingface.co/spaces/preparebuddy/ielts-3b-demo)
-  (free tier — may be slow; pick a section, type, difficulty and topic, and generate).
 ---

 Built by **PrepareBuddy**. A fine-tune of SmolLM3-3B — **not** a from-scratch foundation model.
+**Run it anywhere:**
+- 🖥️ **LM Studio / Ollama / llama.cpp** — the [GGUF build](https://huggingface.co/preparebuddy/ielts-3b-gguf)
+  (Q8_0, runs on Mac / Windows / Linux). **Easiest for most people.**
+- 🍎 **Apple Silicon (MLX)** — the [MLX build](https://huggingface.co/preparebuddy/ielts-3b-mlx)
+  (`mlx-lm`, or LM Studio's MLX runtime).
 - 🐍 **In code** — `transformers` (this repo); see [Usage](#usage-transformers) below.
 - 🌐 **In your browser** — the [demo Space](https://huggingface.co/spaces/preparebuddy/ielts-3b-demo)
+  (free tier — may be slow).
 ---