Instructions to use Elthon5/dipro-rfi-assistant with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Elthon5/dipro-rfi-assistant with Transformers:

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

pipe = pipeline("text-generation", model="Elthon5/dipro-rfi-assistant")

# Load model directly
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM

tokenizer = AutoTokenizer.from_pretrained("Elthon5/dipro-rfi-assistant")
model = AutoModelForSeq2SeqLM.from_pretrained("Elthon5/dipro-rfi-assistant", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Elthon5/dipro-rfi-assistant with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Elthon5/dipro-rfi-assistant"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Elthon5/dipro-rfi-assistant",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/Elthon5/dipro-rfi-assistant

SGLang

How to use Elthon5/dipro-rfi-assistant 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 "Elthon5/dipro-rfi-assistant" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Elthon5/dipro-rfi-assistant",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

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 "Elthon5/dipro-rfi-assistant" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Elthon5/dipro-rfi-assistant",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use Elthon5/dipro-rfi-assistant with Docker Model Runner:
```
docker model run hf.co/Elthon5/dipro-rfi-assistant
```

Elthon5 commited on Jul 16, 2025

Commit

adb12d1

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1 Parent(s): ed340ad

Upload README.md with huggingface_hub

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README.md +1 -5

README.md CHANGED Viewed

@@ -28,9 +28,7 @@ outputs = model.generate(**inputs, max_new_tokens=200, temperature=0.7)
 response = tokenizer.decode(outputs[0], skip_special_tokens=True)
 ```
-## Endpoint API
-Este modelo está disponible a través de la Inference API de Hugging Face:
 ```bash
 curl -X POST \
@@ -41,5 +39,3 @@ curl -X POST \
 ```
 ## Desarrollado por DIPRO
-Modelo especializado para consultas y asistencia virtual.

 response = tokenizer.decode(outputs[0], skip_special_tokens=True)
 ```
+## API Endpoint
 ```bash
 curl -X POST \
 ```
 ## Desarrollado por DIPRO