Update README.md

README.md

@@ -9,23 +9,21 @@ license: mit
 metrics:
 - accuracy
 ---
-# 🇹🇷 Turkish GPT-2 Model
+# Turkish GPT-2 Model (Experimental)
 
-In this repository I release GPT-2 model, that was trained on various texts for Turkish.
+I've made available a GPT-2 model for Turkish that I trained on a variety of texts. 
 
-The model is meant to be an entry point for fine-tuning on other texts.
+The model is intended to serve as a starting point for text-specific adjustments.
 
-## Training corpora
 
-I used a Turkish corpus that is taken from different written and oral sources.
+## Training Source
 
+I used a Turkish corpus that is taken from different written and oral sources.
 
-With the Tokenizers library, I created a 52K BPE vocab based on the training corpus.
 
-After creating the vocab, I could train the GPT-2 for Turkish on over the complete training corpus (five epochs).
+I developed a LLM model with 50k vocabulary using the Custom Tokenizers library using the training resources.
 
-Logs during training:
-https://tensorboard.dev/experiment/3AWKv8bBTaqcqZP5frtGkw/#scalars
+I could train the GPT-2 for Turkish using the entire training corpus (ten epochs) after developing the vocabulary.
 
 
 
@@ -35,16 +33,17 @@ The model itself can be used in this way:
 
 ``` python
 from transformers import AutoTokenizer, AutoModelWithLMHead
-tokenizer = AutoTokenizer.from_pretrained("ahmet1338/gpt2-turkish-cased")
-model = AutoModelWithLMHead.from_pretrained("ahmet1338/gpt2-turkish-cased")
+tokenizer = AutoTokenizer.from_pretrained("ahmet1338/gpt-2-experimental")
+model = AutoModelWithLMHead.from_pretrained("ahmet1338/gpt-2-experimental")
 ```
 
-Here's an example that shows how to use the great Transformers Pipelines for generating text:
+
+To generating text, we can use these lines of code which is Transformers Pipelines:
 
 ``` python
 from transformers import pipeline
-pipe = pipeline('text-generation', model="ahmet1338/gpt2-turkish-cased",
-                 tokenizer="ahmet1338/gpt2-turkish-cased", config={'max_length':800})   
+pipe = pipeline('text-generation', model="ahmet1338/gpt-2-experimental",
+                 tokenizer="ahmet1338/gpt-2-experimental", config={'max_length':800})   
 text = pipe("Akşamüstü yolda ilerlerken, ")[0]["generated_text"]
 print(text)
 ```