karthikqnq/1mgdataset
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This is a custom GPT model based on GPT-2 architecture.
from transformers import AutoModelForCausalLM, AutoTokenizer
model = AutoModelForCausalLM.from_pretrained("karthikqnq/qnqgpt")
tokenizer = AutoTokenizer.from_pretrained("karthikqnq/qnqgpt")
# Generate text
text = "Hello, how are"
inputs = tokenizer(text, return_tensors="pt")
outputs = model.generate(**inputs, max_length=50)
result = tokenizer.decode(outputs[0])
print(result)
[Add your training details here]
[Add model limitations here]
This model is released under the MIT License.