| | --- |
| | 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) |
| |
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| |
|
| | ## Uses |
| |
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| | 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 |
| |
|
| | ```Python |
| | 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 |
| |
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| | ### Training Procedure |
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| |
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| | #### Training Hyperparameters |
| |
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| | - **Adapter:** QLoRA |
| | - **Epochs:** 1 |
| | - **Context length:** 1024 |
| | - **LoRA Rank:** 32 |
| | - **LoRA Alpha:** 32 |
| | - **LoRA Dropout:** 0.05 |
