Instructions to use ThingAI/Quark-270m-Instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use ThingAI/Quark-270m-Instruct with Transformers:

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

pipe = pipeline("text-generation", model="ThingAI/Quark-270m-Instruct", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("ThingAI/Quark-270m-Instruct", trust_remote_code=True, dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use ThingAI/Quark-270m-Instruct with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "ThingAI/Quark-270m-Instruct"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "ThingAI/Quark-270m-Instruct",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/ThingAI/Quark-270m-Instruct

SGLang

How to use ThingAI/Quark-270m-Instruct 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 "ThingAI/Quark-270m-Instruct" \
    --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": "ThingAI/Quark-270m-Instruct",
		"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 "ThingAI/Quark-270m-Instruct" \
        --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": "ThingAI/Quark-270m-Instruct",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use ThingAI/Quark-270m-Instruct with Docker Model Runner:
```
docker model run hf.co/ThingAI/Quark-270m-Instruct
```

ThingsAI commited on 3 days ago

Commit

ec9fbd7

verified ·

1 Parent(s): 845fbeb

Update README.md

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@@ -22,13 +22,6 @@ pipeline_tag: text-generation
 # Quark-270M-Instruct — Bilingual Chat Model
 Quark-270M-Instruct is the **instruction-tuned** version of [Quark-270M Base](https://huggingface.co/ThingAI/Quark-270m-Base), fine-tuned for conversational use in Italian and English. Built entirely from scratch by [ThingsAI](https://things-ai.org).
-### Highlights
-- 🇮🇹🇬🇧 **Bilingual:** Responds naturally in Italian and English
-- 💬 **Conversational:** Greetings, Q&A, general knowledge
-- 💻 **Code-aware:** Python basics and terminal commands
-- 🪶 **Lightweight:** Runs on consumer GPUs (< 1GB VRAM in BF16)
 ## Quick Start
 ```python
@@ -131,24 +124,6 @@ Fine-tuned on a diverse mix of conversational and instructional data:
 Quark-270M-Instruct powers [Things Chat](https://chat.things-ai.org) via a self-hosted FastAPI server with SSE streaming, conversation memory, web search, and content moderation.
-```bash
-QUARK_MODEL_DIR=./Quark-270m-Instruct python app.py
-# → http://localhost:5005
-```
-### API
-```bash
-# Streaming
-curl -X POST http://localhost:5005/api/chat/stream \
-  -H "Content-Type: application/json" \
-  -d '{"text": "Ciao!", "session_id": "user1"}'
-# Batch
-curl -X POST http://localhost:5005/api/chat \
-  -H "Content-Type: application/json" \
-  -d '{"text": "What is AI?"}'
-```
 ## Limitations

 # Quark-270M-Instruct — Bilingual Chat Model
 Quark-270M-Instruct is the **instruction-tuned** version of [Quark-270M Base](https://huggingface.co/ThingAI/Quark-270m-Base), fine-tuned for conversational use in Italian and English. Built entirely from scratch by [ThingsAI](https://things-ai.org).
 ## Quick Start
 ```python
 Quark-270M-Instruct powers [Things Chat](https://chat.things-ai.org) via a self-hosted FastAPI server with SSE streaming, conversation memory, web search, and content moderation.
 ## Limitations