Instructions to use driaforall/Dria-Agent-a-7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use driaforall/Dria-Agent-a-7B with Transformers:

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

pipe = pipeline("text-generation", model="driaforall/Dria-Agent-a-7B")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("driaforall/Dria-Agent-a-7B")
model = AutoModelForCausalLM.from_pretrained("driaforall/Dria-Agent-a-7B")
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]:]))

Inference
Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use driaforall/Dria-Agent-a-7B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "driaforall/Dria-Agent-a-7B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "driaforall/Dria-Agent-a-7B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/driaforall/Dria-Agent-a-7B

SGLang

How to use driaforall/Dria-Agent-a-7B 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 "driaforall/Dria-Agent-a-7B" \
    --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": "driaforall/Dria-Agent-a-7B",
		"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 "driaforall/Dria-Agent-a-7B" \
        --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": "driaforall/Dria-Agent-a-7B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use driaforall/Dria-Agent-a-7B with Docker Model Runner:
```
docker model run hf.co/driaforall/Dria-Agent-a-7B
```

license

by MaziyarPanahi - opened Jan 14, 2025

Discussion

MaziyarPanahi

Jan 14, 2025

Hi,

Thank you for sharing these two models! I just have a quick question regarding the license for the 7B model. I understand why the 3B model is licensed under qwen-research, as it’s based on a model with the same license. However, the 7B model is based on Qwen/Qwen2.5-Coder-7B-Instruct, which is under the Apache 2.0 license.

Is there a specific reason why the 7B model is also licensed as qwen-research?

AtakanTekparmak

Dria org Jan 14, 2025

Hi Maziyar,

Thank you for noticing and letting us know, there was no particular reason, just some overlooking on our part while adding the model card to this model, the license should be Apache 2.0 as the original Qwen/Qwen2.5-Coder-7B-Instruct now.

MaziyarPanahi

Jan 15, 2025

Hi @AtakanTekparmak

Thank you so much for changing the license to Apache 2.0! 🤗

MaziyarPanahi changed discussion status to closed Jan 15, 2025

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