Update README.md

README.md

@@ -1,3 +1,62 @@
 ---
 license: cc-by-nc-4.0
+language:
+- tr
 ---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+gemma-2b fine-tuned for the task of Turkish text generation.
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+- **Language(s) (NLP):** Turkish, English
+- **License:** Creative Commons Attribution Non Commercial 4.0 (Chosen due to the use of restricted/gated datasets.)
+- **Finetuned from model [optional]:** gemma-2b (https://huggingface.co/google/gemma-2b)
+
+
+## Uses
+
+The model is specifically designed for Turkish text generation. It is not suitable for instruction-following or question-answering tasks.
+
+## How to Get Started with the Model
+
+```Python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+tokenizer = AutoTokenizer.from_pretrained("Metin/gemma-2b-tr")
+model = AutoModelForCausalLM.from_pretrained("Metin/gemma-2b-tr")
+
+system_prompt = "You are a helpful assistant. Always reply in Turkish."
+instruction = "Bugün sinemaya gidemedim çünkü"
+prompt = f"{system_prompt} [INST] {instruction} [/INST]"
+input_ids = tokenizer(prompt, return_tensors="pt")
+
+outputs = model.generate(**input_ids)
+print(tokenizer.decode(outputs[0]))
+```
+
+## Training Details
+
+### Training Data
+
+- Dataset size: ~190 Million Token or 100K Document
+- Dataset content: Web crawl data
+
+### Training Procedure
+
+
+#### Training Hyperparameters
+
+- **Adapter:** QLoRA
+- **Epochs:** 1
+- **Context length:** 1024
+- **LoRA Rank:** 32
+- **LoRA Alpha:** 32
+- **LoRA Dropout:** 0.05