Update README.md

README.md

@@ -13,4 +13,24 @@ Based on TransFusion, we introduce GoLLIE-TF, a cross-lingual instruction-tuned
 
 - 📖 Paper: [Translation and Fusion Improves Zero-shot Cross-lingual Information Extraction](https://arxiv.org/abs/2305.13582)
 - 🤗 Model: [GoLLIE-7B-TF](https://huggingface.co/ychenNLP/GoLLIE-7B-TF)
-- 🚀 Example Jupyter Notebooks: [GoLLIE-TF Notebooks](notebooks/tf.ipynb)
+- 🚀 Example Jupyter Notebooks: [GoLLIE-TF Notebooks](notebooks/tf.ipynb)
+
+
+**Important**: This is based on GoLLIE README (Our flash attention implementation has small numerical differences compared to the attention implementation in Huggingface.
+You must use the flag `trust_remote_code=True` or you will get inferior results. Flash attention requires an available CUDA GPU. Running GOLLIE 
+pre-trained models on a CPU is not supported. We plan to address this in future releases. First, install flash attention 2:)
+```bash
+pip install flash-attn --no-build-isolation
+pip install git+https://github.com/HazyResearch/flash-attention.git#subdirectory=csrc/rotary
+```
+
+Then you can load the model using
+
+```python
+import torch
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+tokenizer = AutoTokenizer.from_pretrained("HiTZ/GoLLIE-7B")
+model = AutoModelForCausalLM.from_pretrained("HiTZ/GoLLIE-7B", trust_remote_code=True, torch_dtype=torch.bfloat16)
+model.to("cuda")
+```