Update README.md

Author: shilinyan99

llama_adapter_v2_multimodal/README.md

@@ -1,7 +1,7 @@
 # LLaMA-Adapter-V2 Multi-modal
 
 ## News
-
+* [July 5, 2023] Release pre-traininig and fine-tuning codes.
 * [May 26, 2023] Initial release.
 
 
@@ -23,7 +23,7 @@
   └── tokenizer.model
   ```
 
-## Usage
+## Inference
 
 Here is a simple inference script for LLaMA-Adapter V2. The pre-trained model will be downloaded directly from [Github Release](https://github.com/ZrrSkywalker/LLaMA-Adapter/releases/tag/v.2.0.0).
 
@@ -38,6 +38,7 @@ device = "cuda" if torch.cuda.is_available() else "cpu"
 llama_dir = "/path/to/LLaMA/"
 
 model, preprocess = llama.load("BIAS-7B", llama_dir, device)
+model.eval()
 
 prompt = llama.format_prompt("Please introduce this painting.")
 img = Image.fromarray(cv2.imread("../docs/logo_v1.png"))
@@ -71,4 +72,7 @@ import llama
 print(llama.available_models())
 ```
 
-Now we provide `BIAS-7B`, which fine-tunes the `bias` and `norm` parameters of LLaMA. We will include more pretrained models in the future, such as the LoRA fine-tuning model `LoRA-7B` and partial-tuning model `PARTIAL-7B`.
+Now we provide `BIAS-7B`, which fine-tunes the `bias` and `norm` parameters of LLaMA. We will include more pretrained models in the future, such as the LoRA fine-tuning model `LoRA-7B` and partial-tuning model `PARTIAL-7B`.
+
+## Pre-traininig & Fine-tuning
+See [train.md](docs/train.md)