Update README.md

README.md

@@ -2,6 +2,9 @@
 library_name: peft
 datasets:
 - HachiML/databricks-dolly-15k-ja-for-peft
+language:
+- en
+- ja
 ---
 ## JGLUE Score
 We evaluated our model using the following JGLUE tasks. Here are the scores:
@@ -16,8 +19,34 @@ We evaluated our model using the following JGLUE tasks. Here are the scores:
 - The JGLUE scores were measured using the following script:
 [Stability-AI/lm-evaluation-harness](https://github.com/Stability-AI/lm-evaluation-harness/tree/jp-stable)
 
-## Training procedure
+## How to use
+
+```python
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer, BitsAndBytesConfig, AutoTokenizer
+from peft import PeftModel
+
+model_name = "meta-llama/Llama-2-13b-hf"
+bnb_config = BitsAndBytesConfig(
+    load_in_4bit=True,
+    bnb_4bit_use_double_quant=True,
+    bnb_4bit_quant_type="nf4",
+    bnb_4bit_compute_dtype=torch.float16,
+)
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+pt_model = AutoModelForCausalLM.from_pretrained(
+    model_name,
+    quantization_config=bnb_config,
+)
 
+peft_name = "HachiML/Llama-2-13b-hf-qlora-dolly-ja-2ep"
+model = PeftModel.from_pretrained(
+    pt_model,
+    peft_name,
+)
+```
+
+## Training procedure
 
 The following `bitsandbytes` quantization config was used during training:
 - load_in_8bit: False