Update README.md

README.md

@@ -2604,34 +2604,15 @@ model-index:
       value: 78.25741142443962
 ---
 
-# ember-v1
-
-<p align="center">
-<img src="https://console.llmrails.com/assets/img/logo-black.svg" width="150px">
-</p>
+<h1 align="center">ember-v1</h1>
 
 This model has been trained on an extensive corpus of text pairs that encompass a broad spectrum of domains, including finance, science, medicine, law, and various others. During the training process, we incorporated techniques derived from the [RetroMAE](https://arxiv.org/abs/2205.12035) and [SetFit](https://arxiv.org/abs/2209.11055) research papers.
 
-We are pleased to offer this model as an API service through our platform, [LLMRails](https://llmrails.com/?ref=ember-v1). If you are interested, please don't hesitate to sign up.
-
 ### Plans
 - The research paper will be published soon.
 -  The v2 of the model is currently in development and will feature an extended maximum sequence length of 4,000 tokens.
 
 ## Usage
-Use with API request:
-```bash
-curl --location 'https://api.llmrails.com/v1/embeddings' \
---header 'X-API-KEY: {token}' \
---header 'Content-Type: application/json' \
---data '{
-   "input": ["This is an example sentence"],
-   "model":"embedding-english-v1" # equals to ember-v1
-}'
-```
-API docs: https://docs.llmrails.com/embedding/embed-text<br>
-Langchain plugin: https://python.langchain.com/docs/integrations/text_embedding/llm_rails
-
 Use with transformers:
 ```python
 import torch.nn.functional as F
@@ -2692,4 +2673,15 @@ Our model achieve state-of-the-art performance on [MTEB leaderboard](https://hug
 
 This model exclusively caters to English texts, and any lengthy texts will be truncated to a maximum of 512 tokens.
 
-<img src="https://pixel.llmrails.com/hf/2AtscRthisA1rZzQr8T7Zm">
+## License
+MIT
+
+## Citation
+
+```bibtex
+@misc{nur2024emberv1,
+      title={ember-v1: SOTA embedding model}, 
+      author={Enrike Nur and Anar Aliyev},
+      year={2023},
+}
+```