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README.md

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+# Gemma Model Fine-Tuned on Custom Data
+
+## Model Description
+This model is a fine-tuned version of Gemma Model on custom data. It was trained using the SFTTrainer and incorporates LoRA configurations to enhance performance.
+
+
+
+## Training Procedure
+- **Batch size**: 1
+- **Gradient accumulation steps**: 4
+- **Learning rate**: 2e-4
+- **Warmup steps**: 2
+- **Max steps**: 100
+- **Optimizer**: Paged AdamW 8-bit
+- **FP16**: Enabled
+
+
+## Usage
+You can use this model, Below is an example of how to load and use the model:
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+tokenizer = AutoTokenizer.from_pretrained("username/Gemma_model_fine_tune_custom_Data")
+model = AutoModelForCausalLM.from_pretrained("username/Gemma_model_fine_tune_custom_Data")
+
+input_text = "Your input text here"
+inputs = tokenizer(input_text, return_tensors="pt")
+outputs = model.generate(**inputs)
+
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))