Update README.md

README.md

@@ -1,22 +1,26 @@
-# Decoder Language Model
-Ein kleiner autoregressiver Decoder-only Transformer, trainiert auf Tiny Shakespeare.
-
-## Architektur
-- d_model=128, num_layers=2, nhead=4
-- ~500k Parameter
-
-## Metriken
-- Loss (Train): 0.6342
-- Perplexity (Train): 1.8854
-
-## Laden
-```python
-from transformers import GPT2Tokenizer
-import torch
-from model import DecoderLanguageModel
-
-tokenizer = GPT2Tokenizer.from_pretrained("ahmadisakina/decoder-language-model")
-model = DecoderLanguageModel(vocab_size=tokenizer.vocab_size, d_model=128, nhead=4, num_layers=2)
-model.load_state_dict(torch.load("pytorch_model.bin"))
-model.eval()
+---
+language:
+- en
+---
+# Decoder Language Model
+Ein kleiner autoregressiver Decoder-only Transformer, trainiert auf Tiny Shakespeare.
+
+## Architektur
+- d_model=128, num_layers=2, nhead=4
+- ~500k Parameter
+
+## Metriken
+- Loss (Train): 0.6342
+- Perplexity (Train): 1.8854
+
+## Laden
+```python
+from transformers import GPT2Tokenizer
+import torch
+from model import DecoderLanguageModel
+
+tokenizer = GPT2Tokenizer.from_pretrained("ahmadisakina/decoder-language-model")
+model = DecoderLanguageModel(vocab_size=tokenizer.vocab_size, d_model=128, nhead=4, num_layers=2)
+model.load_state_dict(torch.load("pytorch_model.bin"))
+model.eval()
 ```