Description
This model is a 13.5 billion parameter model that combines four sets of 16 layers each from CALM2-7B.
Note
This model is experimental and may not achieve expected performance without additional tuning.
Tutorial
from transformers import AutoTokenizer, AutoModelForCausalLM
import torch
tokenizer = AutoTokenizer.from_pretrained("sudy-super/baku-13b")
model = AutoModelForCausalLM.from_pretrained("sudy-super/baku-13b", device_map="auto", torch_dtype=torch.bfloat16)
prompt = "大規模言語モデルとは、"
token_ids = tokenizer.encode(prompt, add_special_tokens=False, return_tensors="pt")
with torch.no_grad():
output_ids = model.generate(
token_ids.to(model.device),
max_new_tokens=100,
do_sample=True,
temperature=0.8,
pad_token_id=tokenizer.pad_token_id,
bos_token_id=tokenizer.bos_token_id,
eos_token_id=tokenizer.eos_token_id
)
result = tokenizer.decode(output_ids.tolist()[0])
print(result)