Update README.md

README.md

@@ -7,9 +7,9 @@ datasets:
 This is a modified version of the original LLaMA model that incorporates Scaled Rotary Embeddings first proposed by [kaiokendev](https://kaiokendev.github.io/). By default, the model is configured to be equivalent to the original OpenLLaMA model (2048 context length). To modify, instantiate the LLaMA configuration and set `max_position_embeddings` to the desired context length. The value should be a power of 2, e.g. 2048, 4096, 8192, etc.
 
 ```python
-config = AutoConfig.from_pretrained("emozilla/open_llama_7b-scaled")
+config = AutoConfig.from_pretrained("emozilla/open_llama_7b-scaled", trust_remote_code=True)
 config.max_position_embeddings = 8192
-model = AutoModelForCausalLM.from_pretrained("emozilla/open_llama_7b-scaled", config=config)
+model = AutoModelForCausalLM.from_pretrained("emozilla/open_llama_7b-scaled", config=config, trust_remote_code=True)
 ```
 
 You should also set `max_model_length` on your tokenizer.