Update README.md

README.md

@@ -14,39 +14,6 @@ base_model:
 **Smol-Swallow-1.5B** is a Japanese compact language model created through TAID (Temporally Adaptive Interpolated Distillation), our new knowledge distillation method. 
 We used [Qwen2.5-32B-Instruct](https://huggingface.co/Qwen/Qwen2.5-32B-Instruct) as the teacher model and [Qwen2.5-1.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-1.5B-Instruct) as the student model. 
 The model has been further pre-trained on Japanese text data to enhance its Japanese language capabilities.
-
-## Usage
-
-Use the code below to get started with the model.
-
-<details>
-<summary> Click to expand </summary>
-
-```python
-import torch
-from transformers import AutoModelForCausalLM, AutoTokenizer
-
-
-# 1. load model
-device = "cuda" if torch.cuda.is_available() else "CPU"
-repo_id = "SakanaAI/Smol-Swallow-1.5B"
-model = AutoModelForCausalLM.from_pretrained(repo_id, torch_dtype="auto")
-tokenizer = AutoTokenizer.from_pretrained(repo_id)
-model.to(device)
-
-# 2. prepare inputs
-text = "拝啓\n"
-inputs = tokenizer(text, return_tensors="pt")
-
-# 3. generate
-output_ids = model.generate(**inputs.to(device))
-output_ids = output_ids[:, inputs.input_ids.shape[1] :]
-generated_text = tokenizer.batch_decode(output_ids, skip_special_tokens=True)[0]
-print(generated_text)
-```
-
-</details>
-
  
 ## Model Details