mention how to load v0.1 in readme

README.md

@@ -40,6 +40,11 @@ To build SmolLM-Instruct, we finetuned the base models on publicly available dat
 
 v0.2 models are better at staying on topic and responding appropriately to standard prompts, such as greetings and questions about their role as AI assistants. SmolLM-360M-Instruct (v0.2) has a 63.3% win rate over SmolLM-360M-Instruct (v0.1) on AlpacaEval. You can find the details [here](https://huggingface.co/datasets/HuggingFaceTB/alpaca_eval_details/).
 
+You can load v0.1 checkpoint by specifying `revision="v0.1"` in the transformers code:
+```python
+model = AutoModelForCausalLM.from_pretrained("HuggingFaceTB/SmolLM-1.7B-Instruct", revision="v0.1")
+```
+
 ## Usage
 
 ### Local Applications
@@ -90,6 +95,8 @@ We train the models using the [alignment-handbook](https://github.com/huggingfac
 - warmup ratio 0.1
 - global batch size 262k tokens
 
+You can find the training recipe here: https://github.com/huggingface/alignment-handbook/tree/smollm/recipes/smollm
+
 # Citation
 ```bash
 @misc{allal2024SmolLM,