Create README.md

README.md

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+# phi-1_5-qlora-alpaca-instruction Model Card
+
+## Model Description
+
+This model is a causal language model based on the `microsoft/phi-1_5` and has been finetuned using QLORA technology on the `vicgalle/alpaca-gpt4` dataset.
+
+## Fine-tuning Details
+- **Base Model**: `microsoft/phi-1_5`
+- **Fine-tuning Dataset**: `vicgalle/alpaca-gpt4`
+- **Hardware**: NVIDIA 3090ti
+- **Training Duration**: 8 hours
+- **VRAM Consumption**: Approx. 20 GB for 14 hours
+- **Token Max Length**: 2048
+- **Model Size**: 1.5billion + qlora weights merged
+
+### Hyperparameters
+
+```python
+# Lora Configuration
+config = LoraConfig(
+    r=16,
+    lora_alpha=16,
+    target_modules=["Wqkv", "out_proj"],
+    lora_dropout=0.05,
+    bias="none",
+    task_type="CAUSAL_LM"
+)
+
+# Training Hyperparameters
+training_arguments = TrainingArguments(
+        output_dir=f"{local_path}/output_dir",
+        per_device_train_batch_size=4,
+        gradient_accumulation_steps=6,
+        learning_rate=2e-4,
+        lr_scheduler_type="cosine",
+        evaluation_strategy = "steps",
+        eval_steps=500,
+        save_strategy="epoch",
+        logging_steps=100,
+        num_train_epochs=6,
+        report_to = 'wandb',
+        run_name = run_name
+    )
+
+```
+
+## Usage
+
+```python
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model_name = "nps798/phi-1_5-qlora-alpaca-instruction"
+
+model = AutoModelForCausalLM.from_pretrained(
+    model_name,
+    device_map={"": 0},
+    trust_remote_code=True
+)
+tokenizer = AutoTokenizer.from_pretrained(
+    model_name,
+    trust_remote_code=True
+)
+
+prompt= """Below is an instruction that describes a task. Write a response that appropriately completes the request.
+
+### Instruction:
+Choose three places you would like to visit and explain why.
+
+### Response:"""
+inputs = tokenizer(prompt, return_tensors="pt", return_attention_mask=False)
+outputs = model.generate(**inputs, max_length=500)
+text = tokenizer.batch_decode(outputs)[0]
+print(text)
+
+```
+
+## License
+Because the base model is microsoft phi-1.5b model, this fine-tuned model is provided under the MICROSOFT RESEARCH LICENSE and is meant for non-commercial use only.
+
+## Author
+I am a medical doctor interested in ML/NLP field. 
+If you have any advice, suggestions, or opportunities, or simply want to discuss the fascinating intersection of medicine and technology, please don't hesitate to reach out.
+