Update README.md

README.md

@@ -2,8 +2,104 @@
 library_name: transformers.js
 base_model:
 - prithivMLmods/Lang-Exster-0.5B-Instruct
+license: apache-2.0
+language:
+- en
+pipeline_tag: text-generation
+tags:
+- text-generation-inference
+- code
 ---
 
 # Lang-Exster-0.5B-Instruct (ONNX)
 
 This is an ONNX version of [prithivMLmods/Lang-Exster-0.5B-Instruct](https://huggingface.co/prithivMLmods/Lang-Exster-0.5B-Instruct). It was automatically converted and uploaded using [this space](https://huggingface.co/spaces/onnx-community/convert-to-onnx).
+
+![4.png](https://cdn-uploads.huggingface.co/production/uploads/65bb837dbfb878f46c77de4c/idAWG-bcbdFSmTJdcnIYb.png)
+
+# **Lang-Exster-0.5B-Instruct**
+
+> **Lang-Exster-0.5B-Instruct** is a **general-purpose instruction-following LLM** fine-tuned from **Qwen2.5-0.5B**. This model is optimized for **lightweight deployments** and **instructional clarity**, capable of performing a wide range of natural language and programming-related tasks with efficiency and interpretability.
+
+## **Key Features**
+
+1. **Instruction Following & Explanation**  
+   Trained to **understand, follow, and respond** to natural language instructions with clear, logical, and relevant output. Suitable for Q&A, step-by-step reasoning, and guided code generation.
+
+2. **Lightweight General-Purpose Model**  
+   Fine-tuned from **Qwen2.5-0.5B**, making it **highly efficient for edge devices**, **local tools**, and **low-resource applications** without sacrificing utility.
+
+3. **Multi-Domain Task Handling**  
+   Can perform across **coding**, **writing**, **summarization**, **chat**, **translation**, and **educational queries**, thanks to its broad general-purpose instruction tuning.
+
+4. **Compact and Efficient**  
+   At just **0.5B parameters**, Lang-Exster is optimized for **fast inference**, **low memory usage**, and seamless integration into developer tools and workflows.
+
+5. **Code Assistance (Lite)**  
+   Capable of **basic code generation**, **syntax checking**, and **conceptual explanations**, especially useful for beginners and instructional applications.
+
+## **Quickstart with Transformers**
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model_name = "prithivMLmods/Lang-Exster-0.5B-Instruct"
+
+model = AutoModelForCausalLM.from_pretrained(
+    model_name,
+    torch_dtype="auto",
+    device_map="auto"
+)
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+
+prompt = "Write a Python function that checks if a number is prime, and explain how it works."
+
+messages = [
+    {"role": "system", "content": "You are an instructional assistant. Follow user instructions clearly and explain your reasoning."},
+    {"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]
+```
+
+## **Intended Use**
+
+- **General-Purpose Assistant**:  
+  Performs everyday tasks such as Q&A, summarization, light coding, language generation, and translation.
+
+- **Educational Support**:  
+  Aids learners in understanding topics through **guided explanations**, **basic coding help**, and **concept breakdowns**.
+
+- **Lightweight Developer Integration**:  
+  Ideal for command-line assistants, browser plugins, and desktop utilities with limited compute resources.
+
+- **Instruction Clarity Demonstrator**:  
+  Acts as a fine baseline for developing **instruction-tuned** capabilities in constrained environments.
+
+## **Limitations**
+
+1. **Scale Limitations**  
+   Being a 0.5B model, it has limited memory and may not handle deep context or long documents effectively.
+
+2. **Reasoning Depth**  
+   Provides **surface-level reasoning** and may struggle with highly technical, abstract, or creative prompts.
+
+3. **Basic Code Generation**  
+   Supports basic scripting and logic but may miss edge cases or advanced patterns in complex code.
+
+4. **Prompt Design Sensitivity**  
+   Performs best with **clear**, **concise**, and **well-structured** instructions.