from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Gatescrispy/dippy-dialogpt-optimized")
model = AutoModelForCausalLM.from_pretrained("Gatescrispy/dippy-dialogpt-optimized")

# Generate response
inputs = tokenizer.encode("Hello! How are you today?", return_tensors="pt")
outputs = model.generate(inputs, max_length=50, pad_token_id=tokenizer.eos_token_id)
response = tokenizer.decode(outputs[0], skip_special_tokens=True)
print(response)

Training

Dataset: Custom Dippy personality conversations
Training: 1 epoch with learning rate scheduling
Hardware: NVIDIA RTX 3090

Bittensor Integration

This model is designed for Bittensor SN11 Dippy subnet integration.