Update README.md

README.md

@@ -2,7 +2,60 @@
 library_name: transformers
 datasets:
 - jeanflop/post_ocr_correction-512
+language:
+- fr
+- en
+base_model:
+- google/flan-t5-large
 ---
 
 
-This model has been finetune on french OCR dataset. The architecture used is Flan T large. On a sample of 1000. More stong model is under cooks.
+This model lora weight has been finetune on french OCR dataset. The architecture used is Flan T large. On a sample of 1000. More stong model is under cooks.
+
+* **Install dependencies**
+
+```bash
+!pip install -q transformers accelerate peft diffusers
+```
+* **Load and merge adaptaters in 8Bit** (recommanded)
+
+```
+import torch
+from peft import PeftModel, PeftConfig
+from transformers import AutoModelForSeq2SeqLM, AutoTokenizer,BitsAndBytesConfig
+
+# Load peft config for pre-trained checkpoint etc.
+peft_model_id = "jeanflop/ocr_correcteur-v1"
+config = PeftConfig.from_pretrained(peft_model_id)
+
+# load base LLM model and tokenizer
+peft_model = AutoModelForSeq2SeqLM.from_pretrained(config.base_model_name_or_path,  load_in_8bit=True,  device_map={"":1})
+peft_tokenizer = AutoTokenizer.from_pretrained('google/flan-t5-large')
+
+# Load the Lora model
+peft_model = PeftModel.from_pretrained(peft_model, peft_model_id, device_map={"":1})
+# model.eval()
+
+print("Peft model loaded")
+```
+* **Run inference** (recommanded)
+
+Add your text
+
+```
+inputs=f"""
+Fix text : {text}"""
+```
+Run
+```
+peft_model.config.max_length=512
+peft_tokenizer.model_max_length=512
+inputs = peft_tokenizer(inputs, return_tensors="pt")
+outputs = peft_model.generate(**inputs,max_length=512)
+answer = tokenizer.decode(outputs[0])
+from textwrap import fill
+
+print(fill(answer, width=80))
+```
+
+