Rename the model.

README.md

@@ -4,7 +4,7 @@ license: cc-by-nc-sa-4.0
 
 # LLMLingua-2-Bert-base-Multilingual-Cased-MeetingBank
 
-This model was introduced in the paper [**LLMLingua-2: Data Distillation for Efficient and Faithful Task-Agnostic Prompt Compression** (Pan et al, 2024)](). It is a [XLM-RoBERTa (large-sized model)](https://huggingface.co/FacebookAI/xlm-roberta-large) finetuned to perform token classification for task agnostic prompt compression. The probability $p_{preserve}$ of each token $x_i$ is used as the metric for compression. This model is trained on an extractive text compression dataset constructed with the methodology proposed in the [LLMLingua-2](), using training examples from [MeetingBank (Hu et al, 2023)](https://meetingbank.github.io/) as the seed data.
+This model was introduced in the paper [**LLMLingua-2: Data Distillation for Efficient and Faithful Task-Agnostic Prompt Compression** (Pan et al, 2024)](). It is a [XLM-RoBERTa (large-sized model)](https://huggingface.co/FacebookAI/xlm-roberta-large) finetuned to perform token classification for task agnostic prompt compression. The probability $p_{preserve}$ of each token $x_i$ is used as the metric for compression. This model is trained on [an extractive text compression dataset]() constructed with the methodology proposed in the [LLMLingua-2](), using training examples from [MeetingBank (Hu et al, 2023)](https://meetingbank.github.io/) as the seed data.
 
 For more details, please check the home page of [LLMLingua-2]() and [LLMLingua Series](https://llmlingua.com/).
 
@@ -13,7 +13,7 @@ For more details, please check the home page of [LLMLingua-2]() and [LLMLingua S
 from llmlingua import PromptCompressor
 
 compressor = PromptCompressor(
-        model_name="qianhuiwu/llmlingua-2-xlm-roberta-large-meetingbank",
+        model_name="microsoft/llmlingua-2-xlm-roberta-large-meetingbank",
         use_llmlingua2=True
     )