Update README.md

README.md

@@ -14,86 +14,4 @@ Pico v1 is a work in progress model. Based off Phi 3.5 Mini, it has been fine tu
 
 When making a output, Pico will create three sections, a reasoning section, a self-reflection section and a output section.
 
-Pico v1 struggles with non-question related tasks (Small talk, roleplay, etc).
-
-Here is a example of how you can use it:
-
-```from transformers import AutoModelForCausalLM, AutoTokenizer
-import torch
-
-phi3_template = (
-    "{{ bos_token }}"
-    "{% for message in messages %}"
-        "{{ '<|' + message['role'] + '|>\\n' + message['content'] + '<|end|>\\n' }}"
-    "{% endfor %}"
-    "{% if add_generation_prompt %}"
-        "{{ '<|assistant|>\\n' }}"
-    "{% endif %}"
-)
-phi3_template_eos_token = "<|end|>"
-
-def build_prompt(messages, bos_token="<|start|>", add_generation_prompt=True):
-    """
-    Build a prompt using the PHI 3.5 template.
-    """
-    prompt = bos_token
-    for message in messages:
-        prompt += f"<|{message['role']}|>\n{message['content']}\n<|end|>\n"
-    if add_generation_prompt:
-        prompt += "<|assistant|>\n"
-    return prompt
-
-def chat_with_model():
-    # Load the model and tokenizer
-    model_name = "LucidityAI/Pico-v1-3b"
-    print("Loading model and tokenizer...")
-
-    # Enforce GPU usage
-    if not torch.cuda.is_available():
-        raise RuntimeError("CUDA is not available. Please ensure your GPU and CUDA environment are configured correctly.")
-
-    device = torch.device("cuda")
-    tokenizer = AutoTokenizer.from_pretrained(model_name)
-    model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.float16)
-    print("Model and tokenizer loaded successfully.")
-
-    # Chat loop
-    print("Start chatting with the model! Type 'exit' to quit.")
-    conversation = []
-    while True:
-        user_input = input("You: ")
-        if user_input.lower() == "exit":
-            print("Goodbye!")
-            break
-
-        # Append user's message to the conversation
-        conversation.append({"role": "user", "content": user_input})
-
-        # Build the input prompt using the PHI 3.5 template
-        prompt = build_prompt(conversation, bos_token=tokenizer.bos_token or "<|start|>")
-
-        # Tokenize the input prompt
-        inputs = tokenizer(prompt, return_tensors="pt", truncation=True, max_length=1024).to(device)
-
-        # Generate a response
-        outputs = model.generate(
-            inputs.input_ids,
-            max_length=1024,
-            num_return_sequences=1,
-            temperature=0.5,
-            pad_token_id=tokenizer.eos_token_id
-        )
-
-        # Decode the response
-        response = tokenizer.decode(outputs[0], skip_special_tokens=True)
-
-        # Extract the assistant's reply
-        assistant_reply = response[len(prompt):].strip()
-        print(f"Model: {assistant_reply}")
-
-        # Append the assistant's reply to the conversation
-        conversation.append({"role": "assistant", "content": assistant_reply})
-
-if __name__ == "__main__":
-    chat_with_model()
-```
+Pico v1 struggles with non-question related tasks (Small talk, roleplay, etc).