Update README.md

README.md

@@ -53,12 +53,40 @@ pipeline_tag: text-generation
 ---
 
 <h1 style='text-align: center '>BLOOM LM - 8bit</h1> 
-<h2 style='text-align: center '><em>BigScience Large Open-science Open-access Multilingual Language Model</em> </h2> 
+<h2 style='text-align: center '><em>BigScience Large Open-science Open-access Multilingual Language Model - 8bit</em> </h2> 
 <h3 style='text-align: center '>Model Card</h3>
 <img src="https://s3.amazonaws.com/moonup/production/uploads/1657124309515-5f17f0a0925b9863e28ad517.png" alt="BigScience Logo" width="800" style="margin-left:'auto' margin-right:'auto' display:'block'"/>
 
 Version 1.0 / 26.May.2022
 
-To be announced soon - related paper: https://arxiv.org/abs/2208.07339
+Related paper: https://arxiv.org/abs/2208.07339
 
+## TL;DR
 
+This repository contains 8bit weights of `bloom-1b7` model. You can load this model using `transformers==4.28.0` and `bitsandbytes>0.37.2` out of the box !
+
+```python
+# pip install accelerate bitsandbytes
+from transformers import AutoModelForCausalLM
+
+model = AutoModelForCausalLM.from_pretrained("ybelkada/bloom-1b7-8bit")
+```
+
+## How to push 8bit weights?
+
+First, make sure you are using `transformers` & `bitsandbytes` versions stated above. Then load your 8bit model as usual using `load_in_8bit=True`!
+
+```python
+# pip install accelerate bitsandbytes
+from transformers import AutoModelForCausalLM
+
+model = AutoModelForCausalLM.from_pretrained("bigscience/bloom-1b7", device_map="auto", load_in_8bit=True)
+```
+
+Then just call `push_to_hub` method or `save_pretrained` method if you want to save your 8bit model locally
+
+```python
+model.push_to_hub("{your_username}/bloom-1b7-8bit")
+```
+
+That's it!