Update README.md

README.md

@@ -15,7 +15,7 @@ library_name: PyLate
 metrics:
 - accuracy
 model-index:
-- name: PyLate model based on EuroBERT/EuroBERT-610m
+- name: PyLate model based on EuroBERT/EuroBERT-210m
   results:
   - task:
       type: col-berttriplet
@@ -32,10 +32,11 @@ language:
 - es
 - en
 ---
+[<img src="https://cdn-avatars.huggingface.co/v1/production/uploads/67b2f4e49edebc815a3a4739/R1g957j1aBbx8lhZbWmxw.jpeg" width="200"/>](https://huggingface.co/fjmgAI)
 
 ## Fine-Tuned Model
 
-**`raialvaro/colbert-610M-EuroBERT`**
+**`fjmgAI/col1-610M-EuroBERT`**
 
 ## Base Model
 **`EuroBERT/EuroBERT-610m`**
@@ -71,7 +72,7 @@ import torch
 from pylate import models
 
 # Load the ColBERT model 
-model = models.ColBERT("raialvaro/colbert-610M-EuroBERT", trust_remote_code=True)
+model = models.ColBERT("fjmgAI/col1-610M-EuroBERT", trust_remote_code=True)
 
 # Move the model to GPU if available, otherwise use CPU
 device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
@@ -143,5 +144,7 @@ print(f"Similarity with negative document: {negative_score.item():.4f}")
 This tuned model is designed for **Spanish applications** that require the use of **efficient semantic search** comparing embeddings at the token level with its MaxSim operation, ideal for **question-answering and document retrieval**.
 
 
-- **Developed by:** raialvaro
-- **License:** apache-2.0
+- **Developed by:** fjmgAI
+- **License:** apache-2.0
+
+[<img src="https://github.com/lightonai/pylate/blob/main/docs/img/logo.png?raw=true" width="200"/>](https://github.com/lightonai/pylate)