Model Card for Model ID
gemma-2b fine-tuned for the task of Turkish text generation.
Model Details
Model Description
- 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.
Restrictions
Gemma is provided under and subject to the Gemma Terms of Use found at ai.google.dev/gemma/terms Please refer to the gemma use restrictions before start using the model. https://ai.google.dev/gemma/terms#3.2-use
How to Get Started with the Model
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("Metin/gemma-2b-tr")
model = AutoModelForCausalLM.from_pretrained("Metin/gemma-2b-tr")
prompt = "Bugün sinemaya gidemedim çünkü"
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