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---
license: apache-2.0
language:
- ja
- en
---
## Description
This model is a 10.2 billion parameter model that combines two sets of 24 layers each from [CALM2-7B](https://huggingface.co./cyberagent/calm2-7b) using slerp-merge.
## Note
This model is experimental and may not achieve expected performance without additional tuning.
## Tutorial
```python
from transformers import AutoTokenizer, AutoModelForCausalLM
import torch
tokenizer = AutoTokenizer.from_pretrained("sudy-super/baku-10b")
model = AutoModelForCausalLM.from_pretrained("sudy-super/baku-10b", 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)
``` |