Instructions to use Cialtion/SimpleTool with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Cialtion/SimpleTool with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Cialtion/SimpleTool")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Cialtion/SimpleTool", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use Cialtion/SimpleTool with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Cialtion/SimpleTool" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Cialtion/SimpleTool", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Cialtion/SimpleTool
- SGLang
How to use Cialtion/SimpleTool 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 "Cialtion/SimpleTool" \ --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": "Cialtion/SimpleTool", "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 "Cialtion/SimpleTool" \ --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": "Cialtion/SimpleTool", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Cialtion/SimpleTool with Docker Model Runner:
docker model run hf.co/Cialtion/SimpleTool
Delete rt_tools.py with huggingface_hub
Browse files- rt_tools.py +0 -23
rt_tools.py
DELETED
|
@@ -1,23 +0,0 @@
|
|
| 1 |
-
import json
|
| 2 |
-
|
| 3 |
-
class RTTools:
|
| 4 |
-
# 简化版工具:函数名和参数极短,最大化体现速度优势
|
| 5 |
-
CONTACT_TOOL = {
|
| 6 |
-
"type": "function",
|
| 7 |
-
"function": {
|
| 8 |
-
"name": "add_contact",
|
| 9 |
-
"description": "Add a contact.",
|
| 10 |
-
"parameters": {
|
| 11 |
-
"type": "object",
|
| 12 |
-
"properties": {
|
| 13 |
-
"name": {"type": "string", "description": "Name"},
|
| 14 |
-
"phone": {"type": "string", "description": "Phone"}
|
| 15 |
-
},
|
| 16 |
-
"required": ["name", "phone"]
|
| 17 |
-
}
|
| 18 |
-
}
|
| 19 |
-
}
|
| 20 |
-
|
| 21 |
-
@classmethod
|
| 22 |
-
def get_all(cls):
|
| 23 |
-
return "\n".join([json.dumps(cls.CONTACT_TOOL)])
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|