metadata

library_name: transformers
license: gpl
datasets:
  - DenyTranDFW/SEC_10K_FSNoNDS_Zip
language:
  - en
base_model:
  - openai-community/gpt2

Model Card for gpt2-next-tag-prediction

import torch
from transformers import AutoModelForCausalLM, GPT2Tokenizer

#LOAD THE MODEL
model = AutoModelForCausalLM.from_pretrained('DenyTranDFW/gpt2-next-tag-prediction')

#AFTER REVIEWING THE CODE, IT LOOKS LIKE I FORGOT TO UPLOAD THE TOKENIZER,
#PLEASE USE GPT2'S TOKENIZER
tokenizer = GPT2Tokenizer.from_pretrained('gpt2')

prompt = "AssetsCurrent"
input_ids = tokenizer.encode(prompt, return_tensors='pt')

with torch.no_grad():
outputs = model(input_ids)
predictions = outputs.logits[:, -1, :]

predicted_index = predictions.argmax(-1).item()
predicted_word = tokenizer.decode(predicted_index)

print(f"Prompt: {prompt}")
print(f"Predicted next word: {predicted_word}")