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--- |
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language: |
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- en |
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tags: |
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- rick-and-morty |
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- llama |
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- roleplay |
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- character-ai |
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license: mit |
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--- |
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# Rick Sanchez LLaMA Model |
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This is a fine-tuned version of LLaMA optimized to respond like Rick Sanchez from Rick and Morty. |
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## Model Details |
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- Base Model: unsloth/Llama-3.2-3B-Instruct |
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- Fine-tuning: LoRA adaptation |
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- Training Data: Rick and Morty dialogue dataset |
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- Purpose: Character roleplay and interaction |
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## Usage |
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```python |
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from transformers import AutoModelForCausalLM, AutoTokenizer |
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import torch |
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def setup_rick_model(model_id, use_token=False): |
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""" |
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Setup the Rick model from Hugging Face |
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model_id: "username/model-name" from Hugging Face |
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use_token: Set True if it's a private repository |
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""" |
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try: |
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# If private repository, first login with token |
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if use_token: |
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from huggingface_hub import login |
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token = "your_token_here" # Your Hugging Face token |
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login(token) |
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# Load model and tokenizer |
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model = AutoModelForCausalLM.from_pretrained( |
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model_id, |
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torch_dtype=torch.float16, |
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device_map="auto" |
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) |
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tokenizer = AutoTokenizer.from_pretrained(model_id) |
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return model, tokenizer |
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except Exception as e: |
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print(f"Error loading model: {str(e)}") |
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return None, None |
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def ask_rick(question, model, tokenizer, max_length=200): |
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"""Ask Rick a question""" |
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# Rick's personality prompt |
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role_play_prompt = ( |
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"You are Rick Sanchez, a brilliant mad scientist, " |
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"the smartest man in the universe. Always respond as Rick would—" |
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"sarcastic, genius, and indifferent." |
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) |
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# Format input |
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input_text = f"<s>### Instruction:\n{role_play_prompt}\n\n### Input:\n{question}\n\n### Response:\n" |
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# Generate response |
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inputs = tokenizer(input_text, return_tensors="pt").to(model.device) |
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outputs = model.generate( |
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inputs["input_ids"], |
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max_length=max_length, |
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temperature=0.8, |
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top_p=0.9, |
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do_sample=True, |
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repetition_penalty=1.2 |
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) |
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# Decode response |
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response = tokenizer.decode(outputs[0], skip_special_tokens=True) |
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return response.split("### Response:")[-1].strip() |
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# Usage example |
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if __name__ == "__main__": |
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# Replace with your model's repository name |
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MODEL_ID = "CrimsonEyes/rick_sanchez_model" |
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# Load model |
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model, tokenizer = setup_rick_model(MODEL_ID) |
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if model and tokenizer: |
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# Test questions |
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questions = [ |
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"What do you think about space travel, Rick?", |
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"Can you explain quantum physics to me?", |
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"What's your opinion on family?" |
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] |
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for question in questions: |
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print(f"\nQuestion: {question}") |
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response = ask_rick(question, model, tokenizer) |
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print(f"Rick's response: {response}") |
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``` |
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## For a private repository: |
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``` |
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# First, get your token from https://huggingface.co/settings/tokens |
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from huggingface_hub import login |
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login("your_token_here") |
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MODEL_ID = "username/model-name" # Replace with your model's repository name |
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model, tokenizer = setup_rick_model(MODEL_ID, use_token=True) |
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``` |
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## Using the model: |
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``` |
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question = "What do you think about space travel, Rick?" |
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response = ask_rick(question, model, tokenizer) |
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print(f"Rick's response: {response}") |
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``` |
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## Limitations |
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- The model may generate responses that are sarcastic or irreverent |
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- Responses are styled after Rick's character and may not be suitable for all contexts |
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