#!/usr/bin/env python3 | |
""" | |
Example usage for deepseek-tiny-v0.1 | |
""" | |
import torch | |
from transformers import DeepseekV3ForCausalLM, AutoTokenizer | |
def main(): | |
# Load model and tokenizer | |
print("Loading model...") | |
model = DeepseekV3ForCausalLM.from_pretrained("ChrisMcCormick/deepseek-tiny-v0.1") | |
tokenizer = AutoTokenizer.from_pretrained("ChrisMcCormick/deepseek-tiny-v0.1") | |
# Set to evaluation mode | |
model.eval() | |
# Example prompts | |
prompts = [ | |
"The future of artificial intelligence is", | |
"In a world where technology advances rapidly,", | |
"The most important discovery in science was", | |
] | |
print("\nGenerating text...") | |
for prompt in prompts: | |
inputs = tokenizer(prompt, return_tensors="pt") | |
with torch.no_grad(): | |
outputs = model.generate( | |
**inputs, | |
max_length=50, | |
temperature=0.7, | |
do_sample=True, | |
pad_token_id=tokenizer.eos_token_id | |
) | |
generated_text = tokenizer.decode(outputs[0], skip_special_tokens=True) | |
print(f"Prompt: {prompt}") | |
print(f"Generated: {generated_text}") | |
print("-" * 50) | |
if __name__ == "__main__": | |
main() | |