metadata

library_name: transformers
license: apache-2.0
language:
  - en
  - ja
base_model: Qwen/QwQ-32B-Preview

KARAKURI LM 32B Thinking 2501 Experimental

Model Details

Model Description

Developed by: KARAKURI Inc.
Model type: Causal Language Models
Languages: Japanese
License: Apache 2.0
Finetuned from model: Qwen/QwQ-32B-Preview
Contact: For questions and comments about the model, please email [email protected]
Demo: https://lm.karakuri.cc/

Usage

Run the model

from transformers import AutoModelForCausalLM, AutoTokenizer

model_name = "karakuri-ai/karakuri-lm-32b-thinking-2501-exp"

model = AutoModelForCausalLM.from_pretrained(
    model_name,
    torch_dtype="auto",
    device_map="auto",
)
tokenizer = AutoTokenizer.from_pretrained(model_name)

messages = [
    {"role": "user", "content": "こんにちは。"}
]
input_ids = tokenizer.apply_chat_template(
    messages,
    add_generation_prompt=True,
    return_tensors="pt",
).to(model.device)
outputs = model.generate(input_ids, max_new_tokens=512)
tokenizer.decode(outputs[0][input_ids.shape[-1]:])

Training Details

Training Infrastructure

Hardware: The model was trained on 16 nodes of an Amazon EC2 trn1.32xlarge instance.
Software: We use code based on neuronx-nemo-megatron.

Acknowledgments

This work was supported by the Ministry of Economy, Trade and Industry (METI) and the New Energy and Industrial Technology Development Organization (NEDO) through the Generative AI Accelerator Challenge (GENIAC).

Citation

@misc{karakuri_lm_32b_thinking_2501_exp,
    author       = { {KARAKURI} {I}nc. },
    title        = { {KARAKURI} {LM} 32{B} {T}hinking 2501 {E}xperimental },
    year         = { 2025 },
    url          = { https://huggingface.co./karakuri-ai/karakuri-lm-32b-thinking-2501-exp },
    publisher    = { Hugging Face },
    journal      = { Hugging Face repository }
}