Update README.md

README.md

@@ -32,12 +32,14 @@ We explore supervised multitask pre-training by proposing ***Instruction Pre-Tra
 - Domain-Specific Models Pre-Trained from Llama3-8B:
   - [Finance-Llama3-8B](https://huggingface.co/instruction-pretrain/finance-Llama3-8B)
   - [Biomedicine-Llama3-8B](https://huggingface.co/instruction-pretrain/medicine-Llama3-8B)
+- General Instruction-Augmented Corpora: [general-instruction-augmented-corpora](https://huggingface.co/datasets/instruction-pretrain/general-instruction-augmented-corpora)
+- Domain-Specific Instruction-Augmented Corpora (no finance data to avoid ethical issues): [medicine-instruction-augmented-corpora](https://huggingface.co/datasets/instruction-pretrain/medicine-instruction-augmented-corpora)
 
 
 ## Domain-Adaptive Continued Pre-Training
 Following [AdaptLLM](https://huggingface.co/AdaptLLM/medicine-chat), we augment the domain-specific raw corpora with instruction-response pairs generated by our [context-based instruction synthesizer](https://huggingface.co/instruction-pretrain/instruction-synthesizer).
 
-For example, to chat with the biomedicine-Llama3-8B model:
+### 1. To chat with the biomedicine-Llama3-8B model:
 ```python
 from transformers import AutoModelForCausalLM, AutoTokenizer
 
@@ -63,6 +65,32 @@ pred = tokenizer.decode(outputs[answer_start:], skip_special_tokens=True)
 print(pred)
 ```
 
+### 2. To evaluate our models on the domain-specific tasks
+1. Setup dependencies
+```bash
+git clone https://github.com/microsoft/LMOps
+cd LMOps/adaptllm
+pip install -r requirements.txt
+```
+
+2. Evaluate
+```bash
+DOMAIN='biomedicine'
+
+# if the model can fit on a single GPU: set MODEL_PARALLEL=False
+# elif the model is too large to fit on a single GPU: set MODEL_PARALLEL=True
+MODEL_PARALLEL=False
+
+# number of GPUs, chosen from [1,2,4,8]
+N_GPU=1
+
+# Set as True
+add_bos_token=True
+
+bash scripts/inference.sh ${DOMAIN} 'instruction-pretrain/medicine-Llama3-8B' ${add_bos_token} ${MODEL_PARALLEL} ${N_GPU}
+```
+
+
 ## Citation
 If you find our work helpful, please cite us: