Update README.md

README.md

@@ -43,14 +43,13 @@ and the respons is:
 
 ## Training procedure
 
-Finetune [tiiuae/falcon-7b](https://huggingface.co/tiiuae/falcon-7b) with [ohtaman/kokkai2022](https://huggingface.co/datasets/ohtaman/kokkai2022)(currentry, private) dataset with LoRA.
-The training parameters are
+Finetune [tiiuae/falcon-7b](https://huggingface.co/tiiuae/falcon-7b) with [ohtaman/kokkai2022](https://huggingface.co/datasets/ohtaman/kokkai2022)(currentry, private) dataset using LoRA with following configurations.
 
 |param|value|
 |:--:|:--:|
 |r| 4|
 |lora_alpha| 2|
-|target_modules|- query_key_value<br> - dense<br> - dense_h_to_4h<br> - dense_4h_to_h|
+|target_modules|query_key_value<br>dense<br>dense_h_to_4h<br>dense_4h_to_h|
 |lora_dropout| 0.01|
 |bias| None|
 |task_type| CAUSAL_LM|
@@ -72,12 +71,12 @@ the prompt template is as follows:
 
 ```
 
-### Example Notebook (Colab)
-
-[Colaboratory](https://colab.research.google.com/drive/1oWHM5_DbltvrD27oZL4-fumXChkMkrC5?usp=sharing) (Pro is not needed.)
-
 ### Example Code
 
+You can try the model with [Colaboratory](https://colab.research.google.com/drive/1oWHM5_DbltvrD27oZL4-fumXChkMkrC5?usp=sharing) .
+No Pro or Pro+ is needed.
+The typical code to generate texts with this model is as follows:
+
 ```python
 tokenizer = transformers.AutoTokenizer.from_pretrained(base_model_name, trust_remote_code=True)
 base_model = transformers.AutoModelForCausalLM.from_pretrained(base_model_name, device_map="auto", torch_dtype=torch.bfloat16, trust_remote_code=True)