File size: 987 Bytes
825ad71 9d173c5 825ad71 9d173c5 825ad71 9d173c5 67796ed 9d173c5 825ad71 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 | import torch
from transformers import AutoModelForCausalLM, AutoTokenizer
REPO_ID = "bmax16634/sologpt-v3-150m-base"
def main():
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
tokenizer = AutoTokenizer.from_pretrained(REPO_ID, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(REPO_ID, trust_remote_code=True).to(device)
model.eval()
prompt = "The future of artificial intelligence is"
inputs = tokenizer(prompt, return_tensors="pt").to(device)
with torch.no_grad():
output_ids = model.generate(
**inputs,
max_new_tokens=80,
do_sample=True,
temperature=0.8,
top_k=40,
use_cache=False,
remove_invalid_values=True,
renormalize_logits=True,
pad_token_id=tokenizer.eos_token_id,
)
print(tokenizer.decode(output_ids[0], skip_special_tokens=True))
if __name__ == "__main__":
main()
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