Instructions to use muradil211/ToolWeave_stage1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use muradil211/ToolWeave_stage1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="muradil211/ToolWeave_stage1")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("muradil211/ToolWeave_stage1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use muradil211/ToolWeave_stage1 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "muradil211/ToolWeave_stage1" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "muradil211/ToolWeave_stage1", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/muradil211/ToolWeave_stage1
- SGLang
How to use muradil211/ToolWeave_stage1 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 "muradil211/ToolWeave_stage1" \ --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": "muradil211/ToolWeave_stage1", "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 "muradil211/ToolWeave_stage1" \ --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": "muradil211/ToolWeave_stage1", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use muradil211/ToolWeave_stage1 with Docker Model Runner:
docker model run hf.co/muradil211/ToolWeave_stage1
Add ToolWeave Stage 1 model card and branding
Browse files- README.md +38 -0
- assets/toolweave-mark.svg +22 -0
README.md
ADDED
|
@@ -0,0 +1,38 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
<div align="center">
|
| 2 |
+
|
| 3 |
+
<img src="assets/toolweave-mark.svg" alt="ToolWeave mark" width="110">
|
| 4 |
+
|
| 5 |
+
# ToolWeave Stage 1
|
| 6 |
+
|
| 7 |
+
**Tool-use cold-start checkpoint for multi-turn tool-calling agents.**
|
| 8 |
+
|
| 9 |
+
</div>
|
| 10 |
+
|
| 11 |
+
## Model summary
|
| 12 |
+
|
| 13 |
+
ToolWeave Stage 1 is the first curriculum checkpoint in the ToolWeave project. It is trained to improve parser-compatible tool-call formatting, executable interaction, and stable multi-turn tool-use behavior in the BFCL environment.
|
| 14 |
+
|
| 15 |
+
- Base family: Qwen3-4B-Instruct
|
| 16 |
+
- Curriculum stage: Stage 1 — Tool-Use Cold Start
|
| 17 |
+
- Checkpoint: selected Stage 1 update 25
|
| 18 |
+
- Training signal: format and executable tool-use feedback
|
| 19 |
+
|
| 20 |
+
This repository contains the Stage 1 checkpoint. It is not the final ToolWeave model.
|
| 21 |
+
|
| 22 |
+
## Usage
|
| 23 |
+
|
| 24 |
+
```python
|
| 25 |
+
from transformers import AutoModelForCausalLM, AutoTokenizer
|
| 26 |
+
|
| 27 |
+
model_id = "muradil211/ToolWeave_stage1"
|
| 28 |
+
tokenizer = AutoTokenizer.from_pretrained(model_id)
|
| 29 |
+
model = AutoModelForCausalLM.from_pretrained(model_id, device_map="auto")
|
| 30 |
+
```
|
| 31 |
+
|
| 32 |
+
Tool-use inference requires the model's function schemas and the Qwen3-compatible tool-call format.
|
| 33 |
+
|
| 34 |
+
## Links
|
| 35 |
+
|
| 36 |
+
- [ToolWeave project](https://github.com/Muradil-mamat-211/ToolWeave)
|
| 37 |
+
- [BFCL](https://github.com/ShishirPatil/gorilla/tree/main/berkeley-function-call-leaderboard)
|
| 38 |
+
|
assets/toolweave-mark.svg
ADDED
|
|