Instructions to use foduucom/Think-and-Code-React with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use foduucom/Think-and-Code-React with Transformers:

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

pipe = pipeline("text-generation", model="foduucom/Think-and-Code-React")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("foduucom/Think-and-Code-React")
model = AutoModelForCausalLM.from_pretrained("foduucom/Think-and-Code-React", device_map="auto")
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 Settings

vLLM

How to use foduucom/Think-and-Code-React with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/foduucom/Think-and-Code-React

SGLang

How to use foduucom/Think-and-Code-React 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 "foduucom/Think-and-Code-React" \
    --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": "foduucom/Think-and-Code-React",
		"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 "foduucom/Think-and-Code-React" \
        --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": "foduucom/Think-and-Code-React",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use foduucom/Think-and-Code-React with Docker Model Runner:
```
docker model run hf.co/foduucom/Think-and-Code-React
```

nehulagrawal commited on Mar 8, 2025

Commit

8a17ac4

verified ·

1 Parent(s): b6582e2

Update README.md

Browse files

Files changed (1) hide show

README.md +5 -9

README.md CHANGED Viewed

@@ -46,9 +46,9 @@ Training LLM for React specific dataset and enable reasoning task. This LLM prov
 ## How It Works
-1. **Data Collection**: The model is trained on (Microsoft's Phi4) model output whare 1000s of react specific senerios. it does provide us cold start with good reasoning capabilities
-2. **Feature Extraction**: Upscalling it using RL to enable model with heigh level of accuracy and better output for reasoning.l
 3. **Machine Learning**: A sophisticated machine learning algorithm is employed to learn the heigh quality code in React Specific code and can be expand to all freamwork.
@@ -66,14 +66,10 @@ Training LLM for React specific dataset and enable reasoning task. This LLM prov
 1. Clone this repository:
    ```bash
-   git clone https://huggingface.co/nehulagrawal/baby-cry-classification
-   cd baby-cry-classifier
    ```
-2. Download the pre-trained model files:
-    'model.joblib'
-    'label.joblib'
 ### Usage
 1. Import the necessary libraries:
@@ -125,7 +121,7 @@ For inquiries and contributions, please contact us at info@foduu.com.
 ```bibtex
 @ModelCard{
-    author       = {Nehul Agrawal, Priyal Mata and Ayush Panday},
     title         = {Think and Code in React},
     year           = {2025}
 }

 ## How It Works
+1. **Data Collection**: The model is trained on 1000's of react specific senerios. it does provide us cold start with good reasoning capabilities
+2. **Feature Extraction**: Upscalling it using RL to enable model with heigh level of accuracy and better output for reasoning.
 3. **Machine Learning**: A sophisticated machine learning algorithm is employed to learn the heigh quality code in React Specific code and can be expand to all freamwork.
 1. Clone this repository:
    ```bash
+   git clone https://huggingface.co/foduucom/Think-and-Code-React
+   cd Think-and-Code-React
    ```
 ### Usage
 1. Import the necessary libraries:
 ```bibtex
 @ModelCard{
+    author       = {Nehul Agrawal, Priyal Mehta and Ayush Panday},
     title         = {Think and Code in React},
     year           = {2025}
 }