Update README.md

README.md

@@ -152,8 +152,150 @@ model = PeftModel.from_pretrained(base_model, lora_repo)
 
 ```
 
+```
+python
+
+import torch
 
+# Ensure the model is in evaluation mode
+model.eval()
+
+# Function to format prompts consistently with training data
+def format_prompt(instruction, context=None):
+    if context:
+        return f"Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.\n\n### Instruction:\n{instruction}\n\n### Input:\n{context}\n\n### Response:\n"
+    else:
+        return f"Below is an instruction that describes a task. Write a response that appropriately completes the request.\n\n### Instruction:\n{instruction}\n\n### Response:\n"
 
+# Define a few test prompts
+test_prompts = [
+    {
+        "instruction": "Explain the concept of photosynthesis in simple terms.",
+        "context": None
+    },
+    {
+        "instruction": "What is the capital of France?",
+        "context": None
+    },
+    {
+        "instruction": "Summarize the main idea of the following text:",
+        "context": "The quick brown fox jumps over the lazy dog. This sentence is often used to display all letters of the English alphabet, making it a pangram."
+    },
+    {
+        "instruction": "List three benefits of regular exercise.",
+        "context": None
+    }
+]
+
+# Add the new test prompts (assuming `new_test_prompts` is defined as in the previous step)
+new_test_prompts = [
+    {
+        "instruction": "Write a short, imaginative story about a cat who discovers a secret portal to another dimension under its owner's bed.",
+        "context": None
+    },
+    {
+        "instruction": "If a train leaves New York at 10 AM traveling at 60 mph and another train leaves Chicago at 11 AM traveling at 50 mph, and the cities are 800 miles apart, at what time do they meet? (Assume they are traveling towards each other on the same track).",
+        "context": None
+    },
+    {
+        "instruction": "What is the capital of Australia?",
+        "context": None
+    },
+    {
+        "instruction": "Explain the difference between supervised and unsupervised learning in machine learning, and provide an example of when each would be used.",
+        "context": None
+    },
+    {
+        "instruction": "Summarize the following passage:",
+        "context": "The advent of artificial intelligence has brought forth a new era of technological advancement, impacting various sectors from healthcare to finance. While AI promises increased efficiency and innovative solutions, it also raises ethical concerns regarding job displacement, privacy, and bias in algorithms. Societies worldwide are grappling with how to regulate and integrate AI responsibly, balancing progress with human values. This calls for a multidisciplinary approach involving policymakers, technologists, ethicists, and the public to shape a future where AI serves humanity's best interests."
+    }
+]
+test_prompts.extend(new_test_prompts)
+
+# Generate responses for each test prompt
+print("\n--- Generating Responses ---\n")
+with torch.no_grad():
+    for i, prompt_data in enumerate(test_prompts):
+        instruction = prompt_data["instruction"]
+        context = prompt_data["context"]
+
+        formatted_input = format_prompt(instruction, context)
+
+        # Tokenize the input prompt
+        inputs = tokenizer(formatted_input, return_tensors="pt").to(model.device)
+
+        # Generate response, explicitly using both eos_token_id and pad_token_id
+        outputs = model.generate(
+            **inputs,
+            max_new_tokens=150,  # Limit the length of the generated response
+            do_sample=True,      # Enable sampling for more diverse responses
+            temperature=0.7,     # Control randomness (lower means less random)
+            top_k=50,            # Consider only top 50 probable tokens
+            top_p=0.95,          # Nucleus sampling
+            eos_token_id=tokenizer.eos_token_id,
+            pad_token_id=tokenizer.pad_token_id # Explicitly set pad_token_id
+        )
+
+        # Decode the generated tokens
+        # Exclude the input prompt from the decoded text to get only the model's response
+        generated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
+        response = generated_text[len(formatted_input):].strip()
+
+        print(f"### Test Prompt {i+1}: ###")
+        print(f"Instruction: {instruction}")
+        if context:
+            print(f"Context: {context}")
+        print(f"Model Response: {response}\n")
+
+```
+
+```
+--- Generating Responses ---
+
+### Test Prompt 1: ###
+Instruction: Explain the concept of photosynthesis in simple terms.
+Model Response: Photosynthesis is a process by which plants convert sunlight to carbon dioxide and water. The process is called photosynthesis. When plants are in the green zone, the process of photosynthesis is called "greening". In the process of photosynthesis, plants release oxygen, which can then be used by other organisms. When the process of photosynthesis is not greening, plants do not use oxygen. Plants use carbon dioxide and water to produce food.
+
+### Test Prompt 2: ###
+Instruction: What is the capital of France?
+Model Response: Paris
+
+### Test Prompt 3: ###
+Instruction: Summarize the main idea of the following text:
+Context: The quick brown fox jumps over the lazy dog. This sentence is often used to display all letters of the English alphabet, making it a pangram.
+Model Response: The quick brown fox jumps over the lazy dog.
+
+### Test Prompt 4: ###
+Instruction: List three benefits of regular exercise.
+Model Response: 1. Strengthens muscles
+2. Improves cardiovascular system
+3. Enhances flexibility
+
+### Test Prompt 5: ###
+Instruction: Write a short, imaginative story about a cat who discovers a secret portal to another dimension under its owner's bed.
+Model Response: A cat named Buddy has a new toy for his brother, who lives in another house. When Buddy asks what he can do to help, his owner replies that he could help him move a heavy box into the attic. But the cat can't move the box because it's on the floor. So Buddy says he can help by moving it into the attic.
+
+The cat knows it's in the attic because it heard the owner's voice saying, "Hey, Buddy, move the box," and it knows it's on the floor because it heard the owner saying, "Hey, Buddy, move the box." So the cat knows that the owner is in the attic, and it is in the attic.
+
+### Test Prompt 6: ###
+Instruction: If a train leaves New York at 10 AM traveling at 60 mph and another train leaves Chicago at 11 AM traveling at 50 mph, and the cities are 800 miles apart, at what time do they meet? (Assume they are traveling towards each other on the same track).
+Model Response: The answer is: 12 AM.
+
+### Test Prompt 7: ###
+Instruction: What is the capital of Australia?
+Model Response: Melbourne is the capital of Australia.
+
+### Test Prompt 8: ###
+Instruction: Explain the difference between supervised and unsupervised learning in machine learning, and provide an example of when each would be used.
+Model Response: There are two main differences between supervised and unsupervised learning.  First, supervised learning requires an input to be labeled.  This is typically done with a dataset that you collected and are able to use this dataset to train a model.  Unsupervised learning, on the other hand, does not require any input, but instead relies on the data itself.  This is often done with data that you are not able to collect, such as images or videos.  Another difference is that supervised learning is based on models, whereas unsupervised learning is based on data.  For example, if you have a dataset of pictures of dogs and humans, you can use a supervised learning model to learn about humans, and then use the same model to learn about
+
+### Test Prompt 9: ###
+Instruction: Summarize the following passage:
+Context: The advent of artificial intelligence has brought forth a new era of technological advancement, impacting various sectors from healthcare to finance. While AI promises increased efficiency and innovative solutions, it also raises ethical concerns regarding job displacement, privacy, and bias in algorithms. Societies worldwide are grappling with how to regulate and integrate AI responsibly, balancing progress with human values. This calls for a multidisciplinary approach involving policymakers, technologists, ethicists, and the public to shape a future where AI serves humanity's best interests.
+Model Response: AI promises increased efficiency and innovative solutions, it also raises ethical concerns regarding job displacement, privacy, and bias in algorithms.
+
+
+```
 
 ```
 python