Update README.md

README.md

@@ -24,8 +24,7 @@ widget:
 
 <!-- Provide a quick summary of what the model is/does. -->
 
-This modelcard aims to be a base template for new models. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/modelcard_template.md?plain=1).
-
+Bu model test amaçlı hazırlanmıştır ve fikir vermesi açısından geliştirilmiştir. Model için Vikipedi üzerinden üretilen 40 bin soru cevap GPT ile eğitilmiştir. Daha büyük veri setlerinde daha iyi sonuçlar alınabilir.
 ## Model Details
 
 ### Model Description
@@ -34,12 +33,11 @@ This modelcard aims to be a base template for new models. It has been generated
 
 
 
-- **Developed by:** [More Information Needed]
-- **Shared by [optional]:** [More Information Needed]
+- **Developed by:** Cenker Sisman
 - **Model type:** [More Information Needed]
 - **Language(s) (NLP):** [More Information Needed]
 - **License:** [More Information Needed]
-- **Finetuned from model [optional]:** [More Information Needed]
+- **Finetuned from model  :** redrussianarmy/gpt2-turkish-cased
 
 ### Model Sources [optional]
 
@@ -85,9 +83,41 @@ Users (both direct and downstream) should be made aware of the risks, biases and
 
 ## How to Get Started with the Model
 
-Use the code below to get started with the model.
-
-[More Information Needed]
+"""Inference"""
+
+from transformers import PreTrainedTokenizerFast, GPT2LMHeadModel, GPT2TokenizerFast, GPT2Tokenizer
+
+def load_model(model_path):
+    model = GPT2LMHeadModel.from_pretrained(model_path)
+    return model
+
+
+def load_tokenizer(tokenizer_path):
+    tokenizer = GPT2Tokenizer.from_pretrained(tokenizer_path)
+    return tokenizer
+
+def generate_text(model_path, sequence, max_length):
+    model = load_model(model_path)
+    tokenizer = load_tokenizer(model_path)
+    ids = tokenizer.encode(sequence, return_tensors='pt')
+    outputs = model.generate(
+        ids,
+        do_sample=True,
+        max_length=max_length,
+        pad_token_id=model.config.eos_token_id,
+        top_k=1,
+        top_p=0.99,
+    )
+    converted = tokenizer.convert_ids_to_tokens(outputs[0])
+    valid_tokens = [token if token is not None else '.' for token in converted]
+    generated_text = tokenizer.convert_tokens_to_string(valid_tokens)
+    print(generated_text)
+
+model2_path = "Cenker/turkishgpt"
+sequence2 = "[Q] cengiz han kimdir"
+max_len = 120
+
+generate_text(model2_path, sequence2, max_len)
 
 ## Training Details