|
|
| --- |
| library_name: peft |
| base_model: microsoft/phi-2 |
| tags: |
| - peft |
| - lora |
| - conversational |
| - dark-humor |
| - phi-2 |
| - finetuned |
| license: mit |
| language: en |
| --- |
| |
| # Dark Humor Bot - LoRA Adapter |
|
|
| This is a LoRA adapter fine-tuned on a dark humor dataset. It's designed to generate witty, cynical responses with dark humor. |
|
|
| ## Model Details |
|
|
| - **Base Model:** microsoft/phi-2 |
| - **Fine-tuning Method:** LoRA (Low-Rank Adaptation) |
| - **Training Data:** Custom dark humor conversations |
| - **Training Date:** 2026-03-06 |
| - **Language:** English |
|
|
| ## Description |
|
|
| A fine-tuned phi-2 model for generating dark humor responses |
|
|
| ## Usage |
|
|
| ```python |
| from transformers import AutoTokenizer, AutoModelForCausalLM |
| from peft import PeftModel |
| |
| # Load base model |
| base_model = AutoModelForCausalLM.from_pretrained( |
| "microsoft/phi-2", |
| device_map="auto", |
| torch_dtype=torch.float16 |
| ) |
| tokenizer = AutoTokenizer.from_pretrained("microsoft/phi-2") |
| |
| # Load LoRA adapter |
| model = PeftModel.from_pretrained(base_model, "fausap/dark-phi") |
| |
| # Generate response |
| prompt = "### System: |
| You are a witty, cynical chatbot...\n\n### User:\nTell me a joke\n\n### Assistant:\n" |
| inputs = tokenizer(prompt, return_tensors="pt") |
| outputs = model.generate(**inputs, max_new_tokens=100) |
| response = tokenizer.decode(outputs[0], skip_special_tokens=True) |
| Training Details |
| Quantization: 4-bit QLoRA |
| |
| LoRA Rank: 8 |
| |
| LoRA Alpha: 16 |
| |
| Batch Size: 1 with gradient accumulation |
| |
| Learning Rate: 2e-4 |
| |
| Example Response |
| User: Tell me a dark joke about modern life |
| Assistant: [Generated response will be here] |
| |
| Limitations |
| Optimized for 6GB VRAM |
| |
| May generate inappropriate content (by design - it's dark humor!) |
| |
| Best used with the provided system prompt |
| |
