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download gpt-j

inputs = tokenizer("Hello, I'm", return_tensors="pt") outputs = model.generate(**inputs, max_new_tokens=20) print(tokenizer.decode(outputs[0]))

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")

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 )

Here’s a proper write-up for downloading GPT-J, including the recommended method using Hugging Face Transformers. GPT-J-6B is an open‑source autoregressive language model developed by EleutherAI. It has 6 billion parameters and performs competitively with GPT-3 of similar size. Option 1: Download via Hugging Face 🤗 Transformers (Recommended) This method downloads the model automatically when you load it.