Update README.md

README.md

@@ -1,6 +1,45 @@
 ---
 library_name: peft
 ---
+
+## Model Usage
+
+```python
+import wandb
+import os
+import torch
+
+from transformers import AutoTokenizer, AutoModelForCausalLM, BitsAndBytesConfig, TrainingArguments
+from peft import LoraConfig, prepare_model_for_kbit_training, get_peft_model, AutoPeftModelForCausalLM
+from datasets import load_dataset
+from random import randrange
+from trl import SFTTrainer
+from huggingface_hub import login
+
+
+tokenizer = AutoTokenizer.from_pretrained("Salesforce/codegen25-7b-mono", trust_remote_code=True)
+tokenizer.pad_token = tokenizer.eos_token
+
+device_map = {"":0}
+model = AutoPeftModelForCausalLM.from_pretrained("0xk1h0/codegen2.5-7b-py150k-r20-QLoRA", device_map=device_map, torch_dtype=torch.bfloat16)
+text ="""
+# Generate AES MODE encrypt python function.
+"""
+inputs = tokenizer(text, return_tensors="pt").to("cuda")
+outputs = model.generate(
+    input_ids=inputs["input_ids"].to("cuda"),
+    attention_mask=inputs["attention_mask"],
+    # max_new_tokens=50,
+    max_length=256,
+    do_sample=True,
+    temperature = 0.4,
+    top_p=0.95,
+    pad_token_id=tokenizer.eos_token_id
+    )
+
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+```
+
 ## Training procedure