feat:

README.md

@@ -6,22 +6,23 @@ tags:
 base_model: nomic-ai/modernbert-embed-base
 pipeline_tag: sentence-similarity
 library_name: sentence-transformers
-license: mit
 ---
 
-# ModernBERT Embed Base Distilled
+# SentenceTransformer based on nomic-ai/modernbert-embed-base
 
-This is a [sentence-transformers](https://www.SBERT.net) model distilled from [nomic-ai/modernbert-embed-base](https://huggingface.co/nomic-ai/modernbert-embed-base). It maps sentences & paragraphs to a 256-dimensional dense vector space and can be used for semantic textual similarity, semantic search, paraphrase mining, text classification, clustering, and more.
+This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [nomic-ai/modernbert-embed-base](https://huggingface.co/nomic-ai/modernbert-embed-base). It maps sentences & paragraphs to a 256-dimensional dense vector space and can be used for semantic textual similarity, semantic search, paraphrase mining, text classification, clustering, and more.
 
 ## Model Details
 
 ### Model Description
 - **Model Type:** Sentence Transformer
 - **Base model:** [nomic-ai/modernbert-embed-base](https://huggingface.co/nomic-ai/modernbert-embed-base) <!-- at revision d556a88e332558790b210f7bdbe87da2fa94a8d8 -->
-- **Maximum Sequence Length:** 8 192 tokens
+- **Maximum Sequence Length:** inf tokens
 - **Output Dimensionality:** 256 dimensions
 - **Similarity Function:** Cosine Similarity
-
+<!-- - **Training Dataset:** Unknown -->
+<!-- - **Language:** Unknown -->
+<!-- - **License:** Unknown -->
 
 ### Model Sources
 
@@ -54,7 +55,7 @@ Then you can load this model and run inference.
 from sentence_transformers import SentenceTransformer
 
 # Download from the 🤗 Hub
-model = SentenceTransformer("adrien-riaux/distill-modernbert-embed-base")
+model = SentenceTransformer("AdrienRiaux/distill-modernbert-embed-base")
 # Run inference
 sentences = [
     'The weather is lovely today.',
@@ -109,17 +110,19 @@ You can finetune this model on your own dataset.
 
 ## Training Details
 
-### Distillation Process
-
-The model is distilled using [Model2Vec](https://huggingface.co/blog/Pringled/model2vec) framework. It is a new technique for creating extremely fast and small static embedding models from any Sentence Transformer. 
-
 ### Framework Versions
 - Python: 3.11.9
 - Sentence Transformers: 3.4.1
 - Transformers: 4.48.3
 - PyTorch: 2.2.2
+- Accelerate: 
+- Datasets: 
 - Tokenizers: 0.21.0
 
+## Citation
+
+### BibTeX
+
 <!--
 ## Glossary