Update README.md

README.md

@@ -1,3 +1,88 @@
----
-license: apache-2.0
----
+---
+license: apache-2.0
+---
+
+# **Dorado-WebSurf_Tool-ext**
+
+> **Dorado-WebSurf_Tool-ext** is a **function-calling and agentic reasoning model** fine-tuned from **Qwen3-4B**, designed for **web search orchestration**, **tool-augmented reasoning**, and dynamic **problem-solving**.
+> It excels at **agentic decision-making**, **tool selection**, and structured execution flow, making it ideal for **retrieval-augmented generation (RAG)**, **function calling**, and **tool-based query resolution**.
+
+> [!note]
+> GGUF: [https://huggingface.co/prithivMLmods/Dorado-WebSurf_Tool-ext-GGUF](https://huggingface.co/prithivMLmods/Dorado-WebSurf_Tool-ext-GGUF)
+
+
+## **Key Features**
+
+1. **Agentic Reasoning & Tool-Oriented Execution**
+   Built for orchestrating **function calls**, selecting and sequencing tools, and solving queries through structured multi-step reasoning.
+
+2. **Web Search Query Orchestration**
+   Integrates web search planning, retrieval grounding, and fact-checking, enabling intelligent **query resolution** from live data sources.
+
+3. **Dynamic Tool Selection & Execution Chains**
+   Chooses from an **array of available tools** — including web search, APIs, mathematical solvers, and structured data processors — to solve complex tasks.
+
+4. **Hybrid Symbolic-Probabilistic Logic**
+   Combines structured reasoning with probabilistic inference, ensuring accurate outcomes even in uncertainty-driven or multi-source contexts.
+
+5. **Structured Output Generation**
+   Generates responses in **JSON**, **YAML**, **Markdown**, or **tool call schema formats**, ideal for automation pipelines and agent frameworks.
+
+6. **Optimized Lightweight Footprint**
+   Maintains strong reasoning and tool orchestration capabilities in a **4B parameter model**, deployable on **mid-range GPUs**, **edge devices**, and **offline clusters**.
+
+## **Quickstart with Transformers**
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model_name = "prithivMLmods/Dorado-WebSurf_Tool-ext"
+
+model = AutoModelForCausalLM.from_pretrained(
+    model_name,
+    torch_dtype="auto",
+    device_map="auto"
+)
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+
+prompt = "Find the current weather in Chennai and calculate the probability of rain tomorrow."
+
+messages = [
+    {"role": "system", "content": "You are an intelligent agent capable of reasoning, calling functions, and orchestrating tools for query solving."},
+    {"role": "user", "content": prompt}
+]
+
+text = tokenizer.apply_chat_template(
+    messages,
+    tokenize=False,
+    add_generation_prompt=True
+)
+
+model_inputs = tokenizer([text], return_tensors="pt").to(model.device)
+
+generated_ids = model.generate(
+    **model_inputs,
+    max_new_tokens=512
+)
+generated_ids = [
+    output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)
+]
+
+response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
+print(response)
+```
+
+## **Intended Use**
+
+* Function calling, tool orchestration, and agentic reasoning
+* Web search query resolution and retrieval-based answering
+* Dynamic tool selection and structured problem solving
+* Automation workflows, API integration, and decision-making agents
+* Technical structured output generation for RAG and agent frameworks
+
+## **Limitations**
+
+* Optimized for **tool-assisted** reasoning — less suited for standalone creative writing
+* May require careful prompt engineering for complex multi-tool workflows
+* Tool orchestration performance depends on **external tool availability** and integration quality
+* Context length limits may affect very large multi-document tasks