Shitao commited on
Commit
a7ec0d5
•
1 Parent(s): 465b4b7

Update README.md

Browse files
Files changed (1) hide show
  1. README.md +12 -11
README.md CHANGED
@@ -13,24 +13,29 @@ license: mit
13
  <a href=#usage>Usage</a> |
14
  <a href="#evaluation">Evaluation</a> |
15
  <a href="#train">Train</a> |
16
- <a href="#contact">Contact</a> |
17
  <a href="#citation">Citation</a> |
18
  <a href="#license">License</a>
19
  <p>
20
  </h4>
21
 
22
- More details please refer to our Github: [FlagEmbedding](https://github.com/FlagOpen/FlagEmbedding).
23
 
24
 
25
  [English](README.md) | [中文](https://github.com/FlagOpen/FlagEmbedding/blob/master/README_zh.md)
26
 
27
- FlagEmbedding can map any text to a low-dimensional dense vector which can be used for tasks like retrieval, classification, clustering, or semantic search.
28
- And it also can be used in vector databases for LLMs.
29
 
30
- ************* 🌟**Updates**🌟 *************
31
- - 10/12/2023: Release [LLM-Embedder](./FlagEmbedding/llm_embedder/README.md), a unified embedding model to support diverse retrieval augmentation needs for LLMs. [Paper](https://arxiv.org/pdf/2310.07554.pdf) :fire:
 
 
 
 
 
 
 
32
  - 09/15/2023: The [technical report](https://arxiv.org/pdf/2309.07597.pdf) of BGE has been released
33
- - 09/15/2023: The [masive training data](https://data.baai.ac.cn/details/BAAI-MTP) of BGE has been released
34
  - 09/12/2023: New models:
35
  - **New reranker model**: release cross-encoder models `BAAI/bge-reranker-base` and `BAAI/bge-reranker-large`, which are more powerful than embedding model. We recommend to use/fine-tune them to re-rank top-k documents returned by embedding models.
36
  - **update embedding model**: release `bge-*-v1.5` embedding model to alleviate the issue of the similarity distribution, and enhance its retrieval ability without instruction.
@@ -384,10 +389,6 @@ The data format is the same as embedding model, so you can fine-tune it easily f
384
  More details please refer to [./FlagEmbedding/reranker/README.md](https://github.com/FlagOpen/FlagEmbedding/tree/master/FlagEmbedding/reranker)
385
 
386
 
387
- ## Contact
388
- If you have any question or suggestion related to this project, feel free to open an issue or pull request.
389
- You also can email Shitao Xiao([email protected]) and Zheng Liu([email protected]).
390
-
391
 
392
  ## Citation
393
 
 
13
  <a href=#usage>Usage</a> |
14
  <a href="#evaluation">Evaluation</a> |
15
  <a href="#train">Train</a> |
 
16
  <a href="#citation">Citation</a> |
17
  <a href="#license">License</a>
18
  <p>
19
  </h4>
20
 
21
+ **More details please refer to our Github: [FlagEmbedding](https://github.com/FlagOpen/FlagEmbedding).**
22
 
23
 
24
  [English](README.md) | [中文](https://github.com/FlagOpen/FlagEmbedding/blob/master/README_zh.md)
25
 
26
+ FlagEmbedding focuses on retrieval-augmented LLMs, consisting of the following projects currently:
 
27
 
28
+ - **Fine-tuning of LM** : [LM-Cocktail](https://github.com/FlagOpen/FlagEmbedding/tree/master/LM_Cocktail)
29
+ - **Dense Retrieval**: [LLM Embedder](https://github.com/FlagOpen/FlagEmbedding/tree/master/FlagEmbedding/llm_embedder), [BGE Embedding](https://github.com/FlagOpen/FlagEmbedding/tree/master/FlagEmbedding/baai_general_embedding), [C-MTEB](https://github.com/FlagOpen/FlagEmbedding/tree/master/C_MTEB)
30
+ - **Reranker Model**: [BGE Reranker](https://github.com/FlagOpen/FlagEmbedding/tree/master/FlagEmbedding/reranker)
31
+
32
+
33
+ ## News
34
+
35
+ - 11/23/2023: Release [LM-Cocktail](https://github.com/FlagOpen/FlagEmbedding/tree/master/LM_Cocktail), a method to maintain general capabilities during fine-tuning by merging multiple language models. [Technical Report](https://arxiv.org/abs/2311.13534) :fire:
36
+ - 10/12/2023: Release [LLM-Embedder](https://github.com/FlagOpen/FlagEmbedding/tree/master/FlagEmbedding/llm_embedder), a unified embedding model to support diverse retrieval augmentation needs for LLMs. [Technical Report](https://arxiv.org/pdf/2310.07554.pdf)
37
  - 09/15/2023: The [technical report](https://arxiv.org/pdf/2309.07597.pdf) of BGE has been released
38
+ - 09/15/2023: The [massive training data](https://data.baai.ac.cn/details/BAAI-MTP) of BGE has been released
39
  - 09/12/2023: New models:
40
  - **New reranker model**: release cross-encoder models `BAAI/bge-reranker-base` and `BAAI/bge-reranker-large`, which are more powerful than embedding model. We recommend to use/fine-tune them to re-rank top-k documents returned by embedding models.
41
  - **update embedding model**: release `bge-*-v1.5` embedding model to alleviate the issue of the similarity distribution, and enhance its retrieval ability without instruction.
 
389
  More details please refer to [./FlagEmbedding/reranker/README.md](https://github.com/FlagOpen/FlagEmbedding/tree/master/FlagEmbedding/reranker)
390
 
391
 
 
 
 
 
392
 
393
  ## Citation
394