Update README.md

README.md

@@ -14,9 +14,27 @@ This is part of the Chai reward-model series, using the GPT2 architecture with a
 
 Its training dataset consists of purely user-generated content [retry_and_continue_50m_reward_model](https://huggingface.co/datasets/ChaiML/retry_and_continue_50m_reward_model), where a user has the option to decline the generated response via the retry button or end the conversation.
 
-## Model Details
+## Model details
 - Developed by [Chai Research](https://www.chai-research.com/)
 - Model type: Transformer-based Classification Model
 - Language: English
 - License: cc-by-nc-4.0
-- Contact: to ask questions about this model, join the [Chai Discord](https://discord.com/invite/4KPHkeG6VX). For general correspondence: [[email protected]](mailto:[email protected]?subject=Huggingface%20Model%20Inquiry)
+- Contact: to ask questions about this model, join the [Chai Discord](https://discord.com/invite/4KPHkeG6VX). For general correspondence: [[email protected]](mailto:[email protected]?subject=Huggingface%20Model%20Inquiry)
+
+## Uses and limitations
+### Intended use
+### Out-of-scope use
+### How to use
+
+This reward model can be loaded using the `AutoModelForSequenceClassification` functionality, with a GPT2 tokenizer
+```python
+from transformers import AutoTokenizer, AutoModelForSequenceClassification
+
+tokenizer = AutoTokenizer.from_pretrained("gpt2")
+model = AutoModelForSequenceClassification.from_pretrained("ChaiML/gpt2_base_retry_and_continue_5m_reward_model")
+tokenizer.pad_token_id = 50256
+tokenizer.truncation_side = ‘left’
+tokenizer.padding_side = ‘right’
+tokens = self.eval_tokenizer(candidates, return_tensors='pt', return_attention_mask=True, padding='longest', truncation=True, max_length=256)
+reward = model(**tokens).logits
+```