Update README.md

README.md

@@ -17,7 +17,55 @@ GPT-J-6BをTPUで2週間日本語tokenizerを用いて日本語データで事
 
 ## Uses
 
+```
+pip install transformers sentencepiece accelerate
+```
+
+
 ```python
+from transformers import GPTJForCausalLM, AlbertTokenizer
+import torch
+
+tokenizer = AlbertTokenizer.from_pretrained('AIBunCho/japanese-novel-gpt-j-6b', keep_accents=True, remove_space=False, use_auth_token="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")
+
+model = GPTJForCausalLM.from_pretrained("AIBunCho/japanese-novel-gpt-j-6b", torch_dtype=torch.float16, low_cpu_mem_usage=True, use_auth_token="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")
+
+model.half()
+model.eval()
+
+if torch.cuda.is_available():
+ model = model.to("cuda")
+
+prompt = """
+わたくしといふ現象は
+""".strip()
+
+input_ids = tokenizer.encode(
+ prompt,
+ add_special_tokens=False,
+ return_tensors="pt"
+).cuda()
+
+# this is for reproducibility.
+# feel free to change to get different result
+seed = 27 
+torch.manual_seed(seed)
+
+tokens = model.generate(
+ input_ids.to(device=model.device),
+ max_new_tokens=32,
+ temperature=0.6,
+ top_p=0.9,
+ repetition_penalty=1.2,
+ do_sample=True,
+ pad_token_id=tokenizer.pad_token_id,
+ bos_token_id=tokenizer.bos_token_id,
+ eos_token_id=tokenizer.eos_token_id
+)
+
+out = tokenizer.decode(tokens[0], skip_special_tokens=True)
+print(out)
+"""わたくしといふ現象は、その因果律を断ち切ることができるのです。"""
 
 ```