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README.md

@@ -12057,7 +12057,7 @@ transformers==4.37.2
 from transformers import AutoModel
 import torch
 
-model_name = "OpenBMB/MiniCPM-Embedding-Light"
+model_name = "openbmb/MiniCPM-Embedding-Light"
 model = AutoModel.from_pretrained(model_name, trust_remote_code=True, torch_dtype=torch.float16).to("cuda")
 
 # you can use flash_attention_2 for faster inference
@@ -12114,7 +12114,7 @@ from infinity_emb import AsyncEngineArray, EngineArgs, AsyncEmbeddingEngine
 import numpy as np
 
 array = AsyncEngineArray.from_args([
-  EngineArgs(model_name_or_path = "OpenBMB/MiniCPM-Embedding-Light", engine="torch", dtype="float16", bettertransformer=False, pooling_method="mean", trust_remote_code=True),
+  EngineArgs(model_name_or_path = "openbmb/MiniCPM-Embedding-Light", engine="torch", dtype="float16", bettertransformer=False, pooling_method="mean", trust_remote_code=True),
 ])
 queries = ["中国的首都是哪里？"] # "What is the capital of China?"
 passages = ["beijing", "shanghai"] # "北京", "上海"
@@ -12140,7 +12140,7 @@ print(scores.tolist())  # [[0.40356746315956116, 0.36183443665504456]]
 from FlagEmbedding import FlagModel
 
 
-model = FlagModel("OpenBMB/MiniCPM-Embedding-Light", 
+model = FlagModel("openbmb/MiniCPM-Embedding-Light", 
                           query_instruction_for_retrieval="Query: ",
                           pooling_method="mean",
                           trust_remote_code=True,
@@ -12204,10 +12204,10 @@ print(scores.tolist())  # [[0.40356746315956116, 0.36183440685272217]]
 
 ## 许可证 License
 
-- 本仓库中代码依照 [Apache-2.0 协议](https://github.com/OpenBMB/MiniCPM/blob/main/LICENSE)开源。
-- MiniCPM-Embedding-Light 模型权重的使用则需要遵循 [MiniCPM 模型协议](https://github.com/OpenBMB/MiniCPM/blob/main/MiniCPM%20Model%20License.md)。
+- 本仓库中代码依照 [Apache-2.0 协议](https://github.com/openbmb/MiniCPM/blob/main/LICENSE)开源。
+- MiniCPM-Embedding-Light 模型权重的使用则需要遵循 [MiniCPM 模型协议](https://github.com/openbmb/MiniCPM/blob/main/MiniCPM%20Model%20License.md)。
 - MiniCPM-Embedding-Light 模型权重对学术研究完全开放。如需将模型用于商业用途，请填写[此问卷](https://modelbest.feishu.cn/share/base/form/shrcnpV5ZT9EJ6xYjh3Kx0J6v8g)。
 
-* The code in this repo is released under the [Apache-2.0](https://github.com/OpenBMB/MiniCPM/blob/main/LICENSE) License. 
-* The usage of MiniCPM-Embedding-Light model weights must strictly follow [MiniCPM Model License.md](https://github.com/OpenBMB/MiniCPM/blob/main/MiniCPM%20Model%20License.md).
+* The code in this repo is released under the [Apache-2.0](https://github.com/openbmb/MiniCPM/blob/main/LICENSE) License. 
+* The usage of MiniCPM-Embedding-Light model weights must strictly follow [MiniCPM Model License.md](https://github.com/openbmb/MiniCPM/blob/main/MiniCPM%20Model%20License.md).
 * The models and weights of MiniCPM-Embedding-Light are completely free for academic research. After filling out a ["questionnaire"](https://modelbest.feishu.cn/share/base/form/shrcnpV5ZT9EJ6xYjh3Kx0J6v8g) for registration, MiniCPM-Embedding-Light weights are also available for free commercial use.