tokenizer = AutoTokenizer.from_pretrained(model_name)
from transformers import GPTJForCausalLM, AutoTokenizer model_name = "EleutherAI/gpt-j-6B" model = GPTJForCausalLM.from_pretrained( model_name, revision="float16", # Use float16 version for smaller size torch_dtype=torch.float16, low_cpu_mem_usage=True ) download gpt-j
inputs = tokenizer("Hello, I'm", return_tensors="pt") outputs = model.generate(**inputs, max_new_tokens=20) print(tokenizer.decode(outputs[0])) tokenizer = AutoTokenizer
import torch from transformers import GPTJForCausalLM, AutoTokenizer model = GPTJForCausalLM.from_pretrained("EleutherAI/gpt-j-6B", torch_dtype=torch.float16) tokenizer = AutoTokenizer.from_pretrained("EleutherAI/gpt-j-6B") low_cpu_mem_usage=True ) inputs = tokenizer("Hello