Update README.md

README.md

@@ -7,11 +7,57 @@ language:
 - en
 ---
 ## Style-Instruct Mistral 7B
-Mistral 7B instruct fine-tuned on the [neuralwork/fashion-style-instruct]() dataset with LoRA and 4bit quantization. See the blog [post]() and Github [repository](https://github.com/neuralwork/instruct-finetune-mistral)
-for training details. This model is trained with body type / personal style descriptions as input, target events (e.g. casual date, business meeting) as context and outfit combination suggestions as output.
+Mistral 7B instruct fine-tuned on the [neuralwork/fashion-style-instruct]() dataset with LoRA and 4bit quantization. See the blog [post](https://blog.neuralwork.ai/) and Github [repository](https://github.com/neuralwork/instruct-finetune-mistral)
+for training details. This model is trained with body type / personal style descriptions as input, target events (e.g. casual date, business meeting) as context and outfit combination suggestions as output. For a full list of event types, refer to the gradio demo [file](https://github.com/neuralwork/instruct-finetune-mistral/blob/main/app.py) in the Github repository.
 
 
 ## Usage
 This repo contains the LoRA parameters of the fine-tuned Mistral 7B model. To perform inference, load and use the model as follows:
+
 ```
+import torch
+from peft import AutoPeftModelForCausalLM
+from transformers import AutoTokenizer, AutoModelForCausalLM, BitsAndBytesConfig
+
+
+def format_instruction(input, event):
+    return f"""You are a personal stylist recommending fashion advice and clothing combinations. Use the self body and style description below, combined with the event described in the context to generate 5 self-contained and complete outfit combinations.
+        ### Input:
+        {input}
+
+        ### Context:
+        I'm going to a {event}.
+
+        ### Response:
+    """
+
+# input is a self description of your body type and personal style
+prompt = "I'm an athletic and 171cm tall woman in my mid twenties, I have a rectangle shaped body with slightly broad shoulders and have a sleek, casual style. I usually prefer darker colors."
+event = "business meeting"
+prompt = format_instruction(prompt, event)
+
+# load base LLM model, LoRA params and tokenizer
+model = AutoPeftModelForCausalLM.from_pretrained(
+    "neuralwork/mistral-7b-style-instruct",
+    low_cpu_mem_usage=True,
+    torch_dtype=torch.float16,
+    load_in_4bit=True,
+)
+tokenizer = AutoTokenizer.from_pretrained("neuralwork/mistral-7b-style-instruct")
+input_ids = tokenizer(prompt, return_tensors="pt", truncation=True).input_ids.cuda()
+
+# inference
+with torch.inference_mode():
+    outputs = model.generate(
+        input_ids=input_ids, 
+        max_new_tokens=800, 
+        do_sample=True, 
+        top_p=0.9,
+        temperature=0.9
+    )
+
+# decode output tokens and strip response
+outputs = outputs.detach().cpu().numpy()
+outputs = tokenizer.batch_decode(outputs, skip_special_tokens=True)
+output = outputs[0][len(prompt):]
 ```