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---
base_model:
- cyberagent/DeepSeek-R1-Distill-Qwen-32B-Japanese
- karakuri-ai/karakuri-lm-32b-thinking-2501-exp
- Saxo/Linkbricks-Horizon-AI-Japanese-Base-32B
- FuseAI/FuseO1-DeepSeekR1-Qwen2.5-Coder-32B-Preview
- TeamDelta/ABEJA-Qwen2.5-32B-base-jp-v0.1
- deepseek-ai/DeepSeek-R1-Distill-Qwen-32B
- NovaSky-AI/Sky-T1-32B-Flash
library_name: transformers
tags:
- mergekit
- merge
license: apache-2.0
language:
- en
- ja
---
## 概要
このモデルは[nitky/RoguePlanet-DeepSeek-R1-Qwen-32B](https://huggingface.co/nitky/RoguePlanet-DeepSeek-R1-Qwen-32B)にインスパイアを受け、作成されたモデルです。
<think></tnink>タグが出力されることは確認しています。
日本語モデルとしてもよい性能を出せることも確認しています。
## How To Use
```python
from transformers import AutoModelForCausalLM, AutoTokenizer
model_name = "DataPilot/SKYCAVE-R1-32B-v0.1"
tokenizer_name = ""
if tokenizer_name == "":
tokenizer_name = model_name
model = AutoModelForCausalLM.from_pretrained(
model_name,
torch_dtype="auto",
device_map="auto"
)
tokenizer = AutoTokenizer.from_pretrained(tokenizer_name)
prompt = "メタデータを解析し、自己進化をするAIであるnurture intelligenceが実現した未来の日常生活の姿を教えてください。"
messages = [
{"role": "system", "content": "あなたは優秀な日本語アシスタントであり長考モデルです。問題解決をするための思考をした上で回答を行ってください。"},
{"role": "user", "content": prompt}
]
text = tokenizer.apply_chat_template(
messages,
tokenize=False,
add_generation_prompt=True
)
model_inputs = tokenizer([text], return_tensors="pt").to(model.device)
generated_ids = model.generate(
**model_inputs,
max_new_tokens=4096
)
generated_ids = [
output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)
]
response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
print(response)
```
## 謝辞
このモデルの作成者皆様と、計算資源を貸していただいたVOLTMINDに感謝します。
モデル作成にアドバイスをしていただいたnitkyさんにも感謝申し上げます。
## mergekit config
```yaml
merge_method: slerp
base_model: karakuri-ai/karakuri-lm-32b-thinking-2501-exp
models:
- model: karakuri-ai/karakuri-lm-32b-thinking-2501-exp
- model: Saxo/Linkbricks-Horizon-AI-Japanese-Base-32B
parameters:
t: 0.35
dtype: bfloat16
name: SKYCAVE_element_QwQ_jp
---
merge_method: slerp
base_model: cyberagent/DeepSeek-R1-Distill-Qwen-32B-Japanese
models:
- model: cyberagent/DeepSeek-R1-Distill-Qwen-32B-Japanese
- model: SKYCAVE_element_QwQ_jp
parameters:
t: 0.4
dtype: bfloat16
name: SKYCAVE_element_QR_jp
---
merge_method: slerp
base_model: cyberagent/DeepSeek-R1-Distill-Qwen-32B-Japanese
models:
- model: cyberagent/DeepSeek-R1-Distill-Qwen-32B-Japanese
- model: FuseAI/FuseO1-DeepSeekR1-Qwen2.5-Coder-32B-Preview
parameters:
t: 0.5
dtype: bfloat16
name: SKYCAVE_element_R1_jp_01
---
merge_method: slerp
base_model: cyberagent/DeepSeek-R1-Distill-Qwen-32B-Japanese
models:
- model: cyberagent/DeepSeek-R1-Distill-Qwen-32B-Japanese
- model: TeamDelta/ABEJA-Qwen2.5-32B-base-jp-v0.1
parameters:
t: 0.5
dtype: bfloat16
name: SKYCAVE_element_R1_jp_02
---
merge_method: slerp
base_model: cyberagent/DeepSeek-R1-Distill-Qwen-32B-Japanese
models:
- model: cyberagent/DeepSeek-R1-Distill-Qwen-32B-Japanese
- model: deepseek-ai/DeepSeek-R1-Distill-Qwen-32B
parameters:
t: 0.6
dtype: bfloat16
name: SKYCAVE_element_R1_jp_03
---
merge_method: slerp
base_model: karakuri-ai/karakuri-lm-32b-thinking-2501-exp
models:
- model: karakuri-ai/karakuri-lm-32b-thinking-2501-exp
- model: NovaSky-AI/Sky-T1-32B-Flash
parameters:
t: 0.4
dtype: bfloat16
name: SKYCAVE_element_Sky_jp
---
merge_method: model_stock
base_model: cyberagent/DeepSeek-R1-Distill-Qwen-32B-Japanese
models:
- model: SKYCAVE_element_QR_jp
- model: SKYCAVE_element_R1_jp_01
- model: SKYCAVE_element_R1_jp_02
- model: SKYCAVE_element_R1_jp_03
- model: SKYCAVE_element_Sky_jp
dtype: bfloat16
name: SKYCAVE-R1-32B-v0.1
``` |