Update README.md

README.md

@@ -13,7 +13,7 @@ license: apache-2.0
 
 # Memex: OCR-free Visual Document Embedding Model as Your Personal Librarian
 
-The model only takes images as document-side inputs and produce vectors representing document pages. `minicpm-visual-embedding-v0` is trained with over 200k query-visual document pairs, including textual document, visual document, arxiv figures, plots, charts, industry documents, textbooks, ebooks, and openly-available PDFs, etc. The performance of `minicpm-visual-embedding-v0` is on a par with our ablation text embedding model on text-oriented documents, and an advantages on visually-intensive documents.
+The model only takes images as document-side inputs and produce vectors representing document pages. Memex is trained with over 200k query-visual document pairs, including textual document, visual document, arxiv figures, plots, charts, industry documents, textbooks, ebooks, and openly-available PDFs, etc. Its performance is on a par with our ablation text embedding model on text-oriented documents, and an advantages on visually-intensive documents.
 
 Our model is capable of:
 
@@ -29,11 +29,11 @@ Our model is capable of:
 
 - 2024-07-14: 🤗 We released **online huggingface demo**! Try our [online demo](https://huggingface.co/spaces/bokesyo/minicpm-visual-embeeding-v0-demo)!
 
-- 2024-07-14: 😋 We released a **locally deployable Gradio demo** of `miniCPM-visual-embedding-v0`, take a look at [pipeline_gradio.py](https://huggingface.co/RhapsodyAI/minicpm-visual-embedding-v0/blob/main/pipeline_gradio.py). You can run `pipeline_gradio.py` to build a demo on your PC.
+- 2024-07-14: 😋 We released a **locally deployable Gradio demo** of `Memex`, take a look at [pipeline_gradio.py](https://huggingface.co/RhapsodyAI/minicpm-visual-embedding-v0/blob/main/pipeline_gradio.py). You can run `pipeline_gradio.py` to build a demo on your PC.
 
-- 2024-07-13: 💻 We released a **locally deployable command-line based demo** of `miniCPM-visual-embedding-v0` for users to retireve most relavant pages from a given PDF file (could be very long), take a look at [pipeline.py](https://huggingface.co/RhapsodyAI/minicpm-visual-embedding-v0/blob/main/pipeline.py).
+- 2024-07-13: 💻 We released a **locally deployable command-line based demo** of `Memex` for users to retireve most relavant pages from a given PDF file (could be very long), take a look at [pipeline.py](https://huggingface.co/RhapsodyAI/minicpm-visual-embedding-v0/blob/main/pipeline.py).
 
-- 2024-06-27: 🚀 We released our first visual embedding model checkpoint minicpm-visual-embedding-v0 on [huggingface](https://huggingface.co/RhapsodyAI/minicpm-visual-embedding-v0).
+- 2024-06-27: 🚀 We released our first visual embedding model checkpoint on [huggingface](https://huggingface.co/RhapsodyAI/minicpm-visual-embedding-v0).
 
 - 2024-05-08: 🌍 We [open-sourced](https://github.com/RhapsodyAILab/minicpm-visual-embedding-v0) our training code (full-parameter tuning with GradCache and DeepSpeed, supports large batch size across multiple GPUs with zero-stage1) and eval code. 
 
@@ -161,7 +161,7 @@ If you find our work useful, please consider cite us:
 ```bibtex
 @misc{RhapsodyEmbedding2024,
   author = {RhapsodyAI},
-  title = {OCR-free Visual Document Embedding Model as Your Personal Librarian},
+  title = {Memex: OCR-free Visual Document Embedding Model as Your Personal Librarian},
   year = {2024},
   howpublished = {\url{https://huggingface.co/RhapsodyAI/minicpm-visual-embedding-v0}},
   note = {Accessed: 2024-06-28}