Update README.md

README.md

@@ -1,6 +1,19 @@
- Below is the proper structure formatted to align with Hugging Face's repository conventions, including **tags**, **text**, and other essential metadata.
-
 ---
+license: apache-2.0
+datasets:
+- kanhatakeyama/wizardlm8x22b-logical-math-coding-sft
+base_model:
+- unsloth/Llama-3.2-1B-Instruct
+pipeline_tag: text-generation
+library_name: transformers
+tags:
+- llm
+- maths
+- coding
+- reasoning
+- tech
+---
+ 
 
 # LLaMA-3.2-1B-Instruct Fine-Tuned Model
 
@@ -68,7 +81,7 @@ pip install transformers datasets torch accelerate
 from transformers import AutoModelForCausalLM, AutoTokenizer
 
 # Load the fine-tuned model and tokenizer
-model_name = "your-huggingface-repo/llama-3.2-1b-instruct-finetuned"
+model_name = "ai-nexuz/llama-3.2-1b-instruct-fine-tuned"
 tokenizer = AutoTokenizer.from_pretrained(model_name)
 model = AutoModelForCausalLM.from_pretrained(model_name)
 ```
@@ -87,16 +100,7 @@ print(response)
 
 ---
 
-## Evaluation Metrics
-
-| Metric            | Value          |
-|--------------------|----------------|
-| **Validation Loss** | 1.24          |
-| **Perplexity**     | 3.47          |
-| **Accuracy**       | 92% (logical tasks) |
-| **Code Quality**   | 89% (test cases) |
-
----
+ 
 
 ## Model Training
 
@@ -106,11 +110,8 @@ print(response)
 
 ### Training Configuration
 - **Batch Size**: 32
-- **Learning Rate**: 5e-5
 - **Epochs**: 1
-- **Optimizer**: AdamW
-- **Scheduler**: Linear Decay
-
+ 
 ### Frameworks Used
 - **Unsloth**: For efficient training
 - **Hugging Face Transformers**: For model and tokenizer handling
@@ -149,7 +150,7 @@ This model can also be accessed using the Hugging Face Inference API for hosted
 ```python
 from transformers import pipeline
 
-pipe = pipeline("text-generation", model="your-huggingface-repo/llama-3.2-1b-instruct-finetuned")
+pipe = pipeline("text-generation", model="ai-nexuz/llama-3.2-1b-instruct-fine-tuned")
 result = pipe("Explain the concept of recursion in programming.")
 print(result)
 ```
@@ -189,13 +190,4 @@ This model is released under the **Apache 2.0 License**. See `LICENSE` for detai
 `llama` `fine-tuning` `math` `coding` `logical-reasoning` `instruction-following` `transformers`  
 
 **Summary**:  
-A fine-tuned version of LLaMA-3.2-1B-Instruct specializing in logical reasoning, math problem-solving, and code generation. Perfect for AI-driven tutoring, programming assistance, and logical problem-solving tasks.
-# Uploaded  model
-
-- **Developed by:** user3432234234
-- **License:** apache-2.0
-- **Finetuned from model :** unsloth/llama-3.2-1b-instruct-bnb-4bit
-
-This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
-
-[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
+A fine-tuned version of LLaMA-3.2-1B-Instruct specializing in logical reasoning, math problem-solving, and code generation. Perfect for AI-driven tutoring, programming assistance, and logical problem-solving tasks.