Text Generation
Transformers
Safetensors
English
qwen3
trl
text-generation-inference
agent
tool
web-agent
conversational
Instructions to use prithivMLmods/Dorado-WebSurf_Tool-ext with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prithivMLmods/Dorado-WebSurf_Tool-ext with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="prithivMLmods/Dorado-WebSurf_Tool-ext") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("prithivMLmods/Dorado-WebSurf_Tool-ext") model = AutoModelForCausalLM.from_pretrained("prithivMLmods/Dorado-WebSurf_Tool-ext") 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 prithivMLmods/Dorado-WebSurf_Tool-ext with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "prithivMLmods/Dorado-WebSurf_Tool-ext" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "prithivMLmods/Dorado-WebSurf_Tool-ext", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/prithivMLmods/Dorado-WebSurf_Tool-ext
- SGLang
How to use prithivMLmods/Dorado-WebSurf_Tool-ext 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 "prithivMLmods/Dorado-WebSurf_Tool-ext" \ --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": "prithivMLmods/Dorado-WebSurf_Tool-ext", "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 "prithivMLmods/Dorado-WebSurf_Tool-ext" \ --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": "prithivMLmods/Dorado-WebSurf_Tool-ext", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use prithivMLmods/Dorado-WebSurf_Tool-ext with Docker Model Runner:
docker model run hf.co/prithivMLmods/Dorado-WebSurf_Tool-ext
| { | |
| "_from_model_config": true, | |
| "bos_token_id": 151643, | |
| "do_sample": true, | |
| "eos_token_id": 151645, | |
| "min_p": 0.0, | |
| "temperature": 0.6, | |
| "top_k": 20, | |
| "top_p": 0.95, | |
| "transformers_version": "4.56.1", | |
| "use_cache": false | |
| } | |