Create README.md

README.md

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+---
+language: en
+tags:
+- fine-tuned
+- causal-lm
+- instruction-following
+model_type: causal-lm
+license: mit
+datasets:
+- mlabonne/guanaco-llama2-1k
+metrics:
+- accuracy
+- loss
+---
+
+# Fine-tuned Llama-2 Model on Guanaco Instruction Dataset
+
+## Model Description
+This model is a fine-tuned version of Llama-2 designed specifically for instruction-following tasks. It has been trained on the [Guanaco Llama-2 1k dataset](https://huggingface.co/datasets/mlabonne/guanaco-llama2-1k), enabling it to generate coherent and contextually appropriate responses based on given prompts. This model aims to enhance user interactions through improved understanding of instructions and queries.
+
+## Intended Use
+This model is suitable for various applications, including:
+- Instruction-following tasks
+- Chatbot interactions
+- Text completion based on user prompts
+- Educational tools for generating explanations or summaries
+
+### How to Use
+You can easily load this model using the Transformers library:
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model_name = "gautamraj8044/Llama-2-7b-chat-finetune"  
+
+model = AutoModelForCausalLM.from_pretrained(model_name)
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+
+# Example usage
+input_text = "Please explain the concept of machine learning."
+inputs = tokenizer.encode(input_text, return_tensors="pt")
+outputs = model.generate(inputs)
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))