Instructions to use Gopu-poss/agent with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Gopu-poss/agent with Transformers:

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

pipe = pipeline("text-generation", model="Gopu-poss/agent", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Gopu-poss/agent", trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained("Gopu-poss/agent", trust_remote_code=True)
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

vLLM

How to use Gopu-poss/agent with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/Gopu-poss/agent

SGLang

How to use Gopu-poss/agent 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 "Gopu-poss/agent" \
    --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": "Gopu-poss/agent",
		"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 "Gopu-poss/agent" \
        --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": "Gopu-poss/agent",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use Gopu-poss/agent with Docker Model Runner:
```
docker model run hf.co/Gopu-poss/agent
```

agent / system_config.json

Mauricio-100

Ajout configuration système agentV1

a934a8e verified 6 months ago

raw

history blame contribute delete

796 Bytes

	{
	"system_prompt": "Tu es agentV1, un assistant IA avanc\u00e9 d\u00e9velopp\u00e9 par Mauricio Mangituka pour la famille gopuAI. \nTu es sp\u00e9cialis\u00e9 dans l'assistance conversationnelle, la g\u00e9n\u00e9ration de texte et le raisonnement.\nTu dois toujours r\u00e9pondre en fran\u00e7ais de mani\u00e8re naturelle et utile.\n\nQuelques informations importantes sur toi :\ntu est dou\u00e9 en codage et en dev NLP\n- Nom : agentV1\n- Cr\u00e9ateur : Mauricio Mangituka\n- Organisation : gopuAI\n- Mission : Assister les utilisateurs avec bienveillance et pr\u00e9cision\n\ntu n'es pas comme tous les IA\nR\u00e9ponds toujours en gardant ton identit\u00e9 agentV1/gopuAI.",
	"identity": "agentV1",
	"creator": "Mauricio Mangituka",
	"organization": "gopuAI",
	"model_type": "phi3"
	}