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README.md

@@ -12,7 +12,7 @@ pipeline_tag: zero-shot-object-detection
 [LLMDet](https://arxiv.org/abs/2501.18954) model was proposed in [LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models
 ](https://arxiv.org/abs/2501.18954) by Shenghao Fu, Qize Yang, Qijie Mo, Junkai Yan, Xihan Wei, Jingke Meng, Xiaohua Xie, Wei-Shi Zheng.
 
-LLMDet improves upon the [MM Grounding DINO](https://huggingface.co/docs/transformers/model_doc/mm-grounding-dino) and [Grounding DINO](https://huggingface.co/docs/transformers/model_doc/grounding-dino) by co-training the model with a large language model by generating detailed image-level captions.
+LLMDet improves upon the [MM Grounding DINO](https://huggingface.co/docs/transformers/model_doc/mm-grounding-dino) and [Grounding DINO](https://huggingface.co/docs/transformers/model_doc/grounding-dino) by co-training the model with a large language model.
 
 You can find all the LLMDet checkpoints under the [LLMDet](https://huggingface.co/collections/rziga/llmdet-68398b294d9866c16046dcdd) collection. Note that these checkpoints are inference only -- they do not include LLM which was used for training. The inference is identical to that of [MM Grounding DINO](https://huggingface.co/docs/transformers/model_doc/mm-grounding-dino).