Update README.md

README.md

@@ -6,7 +6,68 @@ tags: []
 # Model Card for Model ID
 
 <!-- Provide a quick summary of what the model is/does. -->
-
+```python
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
+
+# Set a manual seed for reproducibility
+torch.manual_seed(0)
+
+# Load the model with specific configurations
+model = AutoModelForCausalLM.from_pretrained(
+    "AlanYky/phi-3.5_tweets_instruct",
+    device_map="cuda",
+    torch_dtype="auto",
+    trust_remote_code=True
+)
+model.to("cuda")
+
+# Load the tokenizer
+tokenizer = AutoTokenizer.from_pretrained("microsoft/Phi-3.5-mini-instruct")
+
+# Define a function to generate tweets
+def generate_tweet(instruction, pipe, generation_args):
+    """
+    Generate a tweet response based on an instruction.
+    """
+    # Define the message structure
+    messages = [
+        {
+            "role": "user",
+            "content": instruction
+        }
+    ]
+
+    # Generate the tweet response
+    output = pipe(messages, **generation_args)
+
+    # Extract and return the generated tweet text
+    return output[0]['generated_text']
+
+# Set up the pipeline for text generation
+pipe = pipeline(
+    "text-generation",
+    model=model,
+    tokenizer=tokenizer,
+)
+
+# Define generation arguments for tweet creation
+generation_args = {
+    "max_new_tokens": 70,
+    "return_full_text": False,
+    "temperature": 0.4,
+    "top_k": 50,
+    "top_p": 0.9,
+    "repetition_penalty": 1.2,
+    "do_sample": True,
+}
+
+# Specify an instruction for tweet generation
+instruction = "Generate a tweet about Donald Trump is the 2024 US President."
+generated_tweet = generate_tweet(instruction, pipe, generation_args)
+print(generated_tweet)
+
+```
 
 
 ## Model Details