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pytorch_model.bin – the trained model weightsconfig.json – model configurationtokenizer.json – the tokenizergeneration_config.json – generation settings for sampling outputs1from transformers import AutoTokenizer, AutoModelForCausalLM
2import torch
3
4# Load the tokenizer and model
5tokenizer = AutoTokenizer.from_pretrained("DSDUDEd/Dave")
6model = AutoModelForCausalLM.from_pretrained("DSDUDEd/Dave")
7
8# Example prompt
9prompt = "Hey Dave, give me coding advice."
10inputs = tokenizer(prompt, return_tensors="pt")
11
12# Generate output
13outputs = model.generate(**inputs, max_new_tokens=50, do_sample=True, temperature=0.7, top_p=0.9)
14
15# Decode and print
16print(tokenizer.decode(outputs[0], skip_special_tokens=True))