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README.md

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----
-base_model: google/gemma-2-2b-it
-library_name: transformers
-model_name: gemma-2-2B-it-thinking-function_calling-V0
-tags:
-- generated_from_trainer
-- trl
-- sft
-licence: license
----
-
-# Model Card for gemma-2-2B-it-thinking-function_calling-V0
-
-This model is a fine-tuned version of [google/gemma-2-2b-it](https://huggingface.co/google/gemma-2-2b-it).
-It has been trained using [TRL](https://github.com/huggingface/trl).
-
-## Quick start
-
-```python
-from transformers import pipeline
-
-question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?"
-generator = pipeline("text-generation", model="praneethb70/gemma-2-2B-it-thinking-function_calling-V0", device="cuda")
-output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
-print(output["generated_text"])
-```
-
-## Training procedure
-
- 
-
-
-This model was trained with SFT.
-
-### Framework versions
-
-- TRL: 0.25.1
-- Transformers: 4.57.3
-- Pytorch: 2.9.1
-- Datasets: 4.0.0
-- Tokenizers: 0.22.1
-
-## Citations
-
-
-
-Cite TRL as:
-    
-```bibtex
-@misc{vonwerra2022trl,
-	title        = {{TRL: Transformer Reinforcement Learning}},
-	author       = {Leandro von Werra and Younes Belkada and Lewis Tunstall and Edward Beeching and Tristan Thrush and Nathan Lambert and Shengyi Huang and Kashif Rasul and Quentin Gallou{\'e}dec},
-	year         = 2020,
-	journal      = {GitHub repository},
-	publisher    = {GitHub},
-	howpublished = {\url{https://github.com/huggingface/trl}}
-}
-```