Readme file updated

README.md

@@ -1,10 +1,13 @@
 ---
-language: "tr"
+language: tr
 tags:
 - turkish
 - tr
 - gpt2-tr
 - gpt2-turkish
+license: mit
+metrics:
+- accuracy
 ---
 # 🇹🇷 Turkish GPT-2 Model
 
@@ -14,24 +17,17 @@ The model is meant to be an entry point for fine-tuning on other texts.
 
 ## Training corpora
 
-I used a Turkish corpora that is taken from oscar-corpus.
+I used a Turkish corpus that is taken from different written and oral sources.
 
-It was possible to create byte-level BPE with Tokenizers library of Huggingface.
 
-With the Tokenizers library, I created a 52K byte-level BPE vocab based on the training corpora.
+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 two 2080TI over the complete training corpus (five epochs).
+After creating the vocab, I could train the GPT-2 for Turkish on over the complete training corpus (five epochs).
 
 Logs during training:
 https://tensorboard.dev/experiment/3AWKv8bBTaqcqZP5frtGkw/#scalars
 
-## Model weights
 
-Both PyTorch and Tensorflow compatible weights are available.
-
-| Model                             | Downloads
-| --------------------------------- | ---------------------------------------------------------------------------------------------------------------
-| `redrussianarmy/gpt2-turkish-cased`   | [`config.json`](https://huggingface.co/redrussianarmy/gpt2-turkish-cased/resolve/main/config.json) • [`merges.txt`](https://huggingface.co/redrussianarmy/gpt2-turkish-cased/resolve/main/merges.txt) • [`pytorch_model.bin`](https://huggingface.co/redrussianarmy/gpt2-turkish-cased/resolve/main/pytorch_model.bin) • [`special_tokens_map.json`](https://huggingface.co/redrussianarmy/gpt2-turkish-cased/resolve/main/special_tokens_map.json) • [`tf_model.h5`](https://huggingface.co/redrussianarmy/gpt2-turkish-cased/resolve/main/tf_model.h5) • [`tokenizer_config.json`](https://huggingface.co/redrussianarmy/gpt2-turkish-cased/resolve/main/tokenizer_config.json) • [`traning_args.bin`](https://huggingface.co/redrussianarmy/gpt2-turkish-cased/resolve/main/training_args.bin) • [`vocab.json`](https://huggingface.co/redrussianarmy/gpt2-turkish-cased/resolve/main/vocab.json)
 
 ## Using the model
 
@@ -39,16 +35,16 @@ The model itself can be used in this way:
 
 ``` python
 from transformers import AutoTokenizer, AutoModelWithLMHead
-tokenizer = AutoTokenizer.from_pretrained("redrussianarmy/gpt2-turkish-cased")
-model = AutoModelWithLMHead.from_pretrained("redrussianarmy/gpt2-turkish-cased")
+tokenizer = AutoTokenizer.from_pretrained("ahmet1338/gpt2-turkish-cased")
+model = AutoModelWithLMHead.from_pretrained("ahmet1338/gpt2-turkish-cased")
 ```
 
 Here's an example that shows how to use the great Transformers Pipelines for generating text:
 
 ``` python
 from transformers import pipeline
-pipe = pipeline('text-generation', model="redrussianarmy/gpt2-turkish-cased",
-                 tokenizer="redrussianarmy/gpt2-turkish-cased", config={'max_length':800})   
+pipe = pipeline('text-generation', model="ahmet1338/gpt2-turkish-cased",
+                 tokenizer="ahmet1338/gpt2-turkish-cased", config={'max_length':800})   
 text = pipe("Akşamüstü yolda ilerlerken, ")[0]["generated_text"]
 print(text)
 ```
@@ -56,8 +52,6 @@ print(text)
 ### How to clone the model repo?
 ```
 git lfs install
-git clone https://huggingface.co/redrussianarmy/gpt2-turkish-cased
+git clone https://huggingface.co/ahmet1338/gpt2-turkish-cased
 ```
 
-## Contact (Bugs, Feedback, Contribution and more)
-For questions about the GPT2-Turkish model, just open an issue [here](https://github.com/redrussianarmy/gpt2-turkish/issues) 🤗