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 Requirements:
 1- A working tensorflow installation.
 2- The pytorch library: pip install torch
 3- The transformers library: pip install transformers
 4- The model file (pytorch_model.bin). HuggingFace deleted it, but you can download it by torrent: https://archive.org/details/gpt4chan_model
 5- The model config file (config.json). It should be placed in the same folder as the model file and can be found here: https://github.com/yk/gpt-4chan-public
 6- A computer with 24GB of free RAM. A GPU is not required. The model will be executed directly from the CPU.
 
 The folder structure will look like this:
 
 gpt4chan_model
   \_ pytorch_model.bin
   \_ config.json
   \_ CITATION.bib
   \_ gpt4chan_model_meta.sqlite
   \_ gpt4chan_model_meta.xml
   \_ LICENSE.txt
 
 Then execute the model with the following Python script, making sure to place it in the same parent folder as the gpt4chan_model folder:
 
 
 from transformers import AutoModelForCausalLM, AutoTokenizer
 import sys
 import time
 
 model = AutoModelForCausalLM.from_pretrained("gpt4chan_model", low_cpu_mem_usage=True)
 tokenizer = AutoTokenizer.from_pretrained("EleutherAI/gpt-j-6B")
 
 prompt = ("-----\n--- 865467536\nAI is interesting because ")
 input_ids = tokenizer(prompt, return_tensors="pt").input_ids
 
 gen_tokens = model.generate(
     input_ids,
     do_sample=True,
     temperature=0.8,
     top_p=1,
     typical_p=0.3,
     max_length=128,
 )
 
 gen_text = tokenizer.batch_decode(gen_tokens)[0]
 print(gen_text)
 
 
 It takes a few minutes to run the script above.
 In case config.json is taken down, here are its contents:
 
 
 {
   "activation_function": "gelu_new",
   "architectures": [
     "GPTJForCausalLM"
   ],
   "attn_pdrop": 0.0,
   "bos_token_id": 50256,
   "embd_pdrop": 0.0,
   "eos_token_id": 50256,
   "gradient_checkpointing": false,
   "initializer_range": 0.02,
   "layer_norm_epsilon": 1e-05,
   "model_type": "gptj",
   "n_embd": 4096,
   "n_head": 16,
   "n_layer": 28,
   "n_positions": 2048,
   "rotary_dim": 64,
   "summary_activation": null,
   "summary_first_dropout": 0.1,
   "summary_proj_to_labels": true,
   "summary_type": "cls_index",
   "summary_use_proj": true,
   "transformers_version": "4.10.0.dev0",
   "tokenizer_class": "GPT2Tokenizer",
   "task_specific_params": {
     "text-generation": {
       "do_sample": true,
       "temperature": 1.0,
       "max_length": 50
     }
   },
   "torch_dtype": "float32",
   "use_cache": true,
   "vocab_size": 50400
 }