Add pipeline tag and link to Github repository

This PR adds the `pipeline_tag: text-generation` to the model card metadata. This will improve discoverability of the model on the Hugging Face Hub.
It also adds a link to the Github repository.

README.md

@@ -1,23 +1,23 @@
 ---
-license: mit
-library_name: transformers
 base_model:
 - meta-llama/Llama-3.1-8B
+library_name: transformers
+license: mit
+pipeline_tag: text-generation
 ---
+
 # TokenButler
 <!-- markdownlint-disable first-line-h1 -->
 <!-- markdownlint-disable html -->
 <!-- markdownlint-disable no-duplicate-header -->
 
-
-
 <div align="center">
   <img src="https://github.com/abdelfattah-lab/TokenButler/blob/main/figs/tokenbutlerlogo.png?raw=true" width="50%" alt="TokenButler" />
 </div>
 <hr>
 <div align="center" style="line-height: 1;">
   <!-- Paper Badge -->
-  <a href="https://github.com/abdelfattah-lab/TokenButler/blob/main/TokenButler_Draft.pdf" target="_blank" style="margin: 2px;">
+  <a href="https://arxiv.org/abs/2503.07518" target="_blank" style="margin: 2px;">
     <img alt="Paper" 
          src="https://img.shields.io/badge/Paper-View-orange?logo=readthedocs&logoColor=white" 
          style="display: inline-block; vertical-align: middle;"/>
@@ -32,10 +32,9 @@ base_model:
 
 <br>
 
-
 The collection of TokenButler models can be found [here](https://huggingface.co/collections/akhauriyash/tokenbutler-67cf181b5762d0d60e5f312b). To run the `meta-llama/Llama-3.1-8B` model, follow:
 
-```
+```python
 from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline
 
 question = "If millionaires have butlers, why don't million dollar language models have a butler too? I think its because "
@@ -52,7 +51,7 @@ print(response[0]['generated_text'][len(question):])
 
 Note that the 'default' configured sparsity is 50%. Further, there is a 'sliding window' of 128 and 8 'anchor tokens'. To 'change' the sparsity, you can use the following function after loading the model. Please note that the 'fixed' is the only supported strategy at the moment, which 'fixes' the sparsity of each layer (except the first) at the 'pc' (percentage) mentioned. This can also be found at `test_hf.py`. Sliding window and anchor tokens can be changed in a similar manner.
 
-```
+```python
 def set_sparsity(model, sparsity):
     for module in model.modules():
         if module.__class__.__name__.__contains__("AttentionExperimental"):
@@ -63,7 +62,6 @@ def set_sparsity(model, sparsity):
 model = set_sparsity(model, "fixed_60pc")
 ```
 
-
 # Predictor Architecture
 <div align="center">
   <img src="https://github.com/abdelfattah-lab/TokenButler/blob/main/figs/mainfig.png?raw=true" width="100%" alt="TokenButlerFigure" />