Add transformers tag and example code snippet (#2)

- Add transformers tag and example code snippet (8939f06539dee2a50743fb58271eb82a2fc32f0f)


Co-authored-by: Sergio Paniego <sergiopaniego@users.noreply.huggingface.co>

README.md

@@ -1,9 +1,13 @@
----
-license: cc-by-nc-4.0
-base_model:
-- Qwen/Qwen3-1.7B
-- google/siglip2-so400m-patch14-384
----
+---
+license: cc-by-nc-4.0
+base_model:
+- Qwen/Qwen3-1.7B
+- google/siglip2-so400m-patch14-384
+library_name: transformers
+tags:
+- perceptron
+- issac-0.1
+---
 
 # [Isaac-0.1 by Perceptron](https://www.perceptron.inc/blog/introducing-isaac-0-1)
 *Note this is the Post-trained model* [Try out the model on our playground](https://www.perceptron.inc/demo)
@@ -37,8 +41,26 @@ A new interaction pattern where language and vision stay in lockstep: every clai
 ![grounding](https://framerusercontent.com/images/2T1Th5SaXdYhNKyxzd2ge61diA.png?width=1736&height=1260)
 
 ## Example 
+
 ```bash
 pip install perceptron
 ```
 
-[Huggingface Example Repo](https://github.com/perceptron-ai-inc/perceptron/tree/main/huggingface)
+## Example using transformers
+
+Learn more: [Huggingface Example Repo](https://github.com/perceptron-ai-inc/perceptron/tree/main/huggingface)
+
+```bash
+!git clone https://github.com/perceptron-ai-inc/perceptron.git
+!cp -r perceptron/huggingface ./huggingface
+```
+
+```python
+from transformers import AutoTokenizer, AutoConfig, AutoModelForCausalLM
+from huggingface.modular_isaac import IsaacProcessor
+
+tokenizer = AutoTokenizer.from_pretrained("PerceptronAI/Isaac-0.1", trust_remote_code=True, use_fast=False)
+config = AutoConfig.from_pretrained("PerceptronAI/Isaac-0.1", trust_remote_code=True)
+processor = IsaacProcessor(tokenizer=tokenizer, config=config)
+model = AutoModelForCausalLM.from_pretrained("PerceptronAI/Isaac-0.1", trust_remote_code=True)
+```