Update README.md

README.md

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----
-license: apache-2.0
----
+---
+license: apache-2.0
+base_model:
+- prithivMLmods/Sombrero-Opus-14B-Elite6
+pipeline_tag: text-generation
+library_name: transformers
+tags:
+- text-generation-inference
+- code
+- math
+- R1
+language:
+- en
+---
+
+![2.png](https://cdn-uploads.huggingface.co/production/uploads/65bb837dbfb878f46c77de4c/IUa2oAhsMWrD9qwTrEEAD.png)
+
+# **La-Superba-14B-Y.2**
+
+> **La-Superba-14B-Y.2** is a next-generation language model built on the Qwen 2.5 14B architecture. It is meticulously optimized for **mathematical reasoning**, **programming**, and **general-purpose logic-based tasks**. With its advanced comprehension, structured problem-solving capabilities, and long-context handling, it serves as a powerful assistant for technical, educational, and reasoning-intensive workflows.
+
+## **Key Improvements**
+1. **Exceptional Mathematical Reasoning**  
+   Specially trained for handling symbolic math, arithmetic, algebra, calculus, and applied mathematics with step-by-step clarity and logical precision.
+
+2. **Advanced Coding & Debugging Intelligence**  
+   Proficient in code generation, multi-language programming support (Python, JavaScript, C++, etc.), and automatic debugging. It can explain, optimize, and refactor code with minimal prompting.
+
+3. **Superior General-Purpose Reasoning**  
+   Fine-tuned to manage logical deduction, multi-step reasoning, and contextual understanding across a wide array of domains.
+
+4. **Instruction-Following Accuracy**  
+   Capable of precisely interpreting nested, multi-part instructions and returning structured, coherent responses that follow the prompt intent faithfully.
+
+5. **Extended Context Support**  
+   Handles up to **128K tokens** of input with **8K token** output capacity, making it suitable for long documents, codebases, and detailed walkthroughs.
+
+   
+## **Quickstart with Transformers**
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model_name = "prithivMLmods/La-Superba-14B-Y.2"
+
+model = AutoModelForCausalLM.from_pretrained(
+    model_name,
+    torch_dtype="auto",
+    device_map="auto"
+)
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+
+prompt = "Write a Python function to check whether a number is prime and explain each step."
+messages = [
+    {"role": "system", "content": "You are a highly capable assistant in math, programming, and logical 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**
+
+1. **Mathematical Problem Solving**  
+   Solves math questions with detailed steps, symbolic manipulation, and numerical precision—ideal for students, educators, and professionals.
+
+2. **Programming & Automation**  
+   Assists in writing clean, correct code and helps debug and explain errors in software development tasks.
+
+3. **Technical Support and Tutoring**  
+   Can be deployed as a tutor or assistant in educational platforms focused on logic, STEM, and engineering disciplines.
+
+4. **General-Purpose Reasoning Agent**  
+   Useful in applications requiring thoughtful multi-turn reasoning, structured outputs, and logical consistency.
+
+5. **Multilingual Knowledge Assistant**  
+   Enables intelligent communication and content generation across various languages and technical contexts.
+
+6. **Structured and Long-Form Output**  
+   Can produce well-formatted JSON, tables, documents, and full-length guides and reports while maintaining coherence.
+
+## **Limitations**
+
+1. **High Hardware Demand**  
+   Best performance requires high-RAM GPUs or TPUs due to its parameter size and context window.
+
+2. **Bias and Factual Limits**  
+   Some inherited training data biases and occasional factual inaccuracies may still appear.
+
+3. **Not Real-Time Aware**  
+   It does not have access to current events or real-time information post-training.
+
+4. **Creative Limitations**  
+   Less consistent with storytelling, poetry, or heavily subjective tasks.
+
+5. **Prompt Sensitivity**  
+   Output quality and structure can vary based on prompt clarity and format.