Edit model card

Please following paper's format to use this model.

input: SPRiNGSと最も仲の良いライバルグループ。 <社会><文芸><学問><技術><自然> 固有表現抽出

output: <社会>固有表現抽出:その他の組織名;SPRiNGS

generated_ids = model.generate(inputs, max_new_tokens=2000) #Don't need any other set, just max new tokens.

paper cite: https://arxiv.org/abs/2311.06838

bib: @misc{gan2023giellm, title={GIELLM: Japanese General Information Extraction Large Language Model Utilizing Mutual Reinforcement Effect}, author={Chengguang Gan and Qinghao Zhang and Tatsunori Mori}, year={2023}, eprint={2311.06838}, archivePrefix={arXiv}, primaryClass={cs.CL} }

Downloads last month
14
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Collection including ganchengguang/GIELLM-13B-jpllm