Improve language tag

README.md

@@ -1,58 +1,72 @@
----
-base_model: Qwen/Qwen2.5-7B-Instruct
-datasets: AlekseyKorshuk/ai-detection-gutenberg-human-v2-formatted-ai-sft
-library_name: transformers
-model_name: ai-detection-gutenberg-human-v2-formatted-ai-sft-qwen-7b-sft-3epochs
-tags:
-- generated_from_trainer
-- trl
-- sft
-licence: license
----
-
-# Model Card for ai-detection-gutenberg-human-v2-formatted-ai-sft-qwen-7b-sft-3epochs
-
-This model is a fine-tuned version of [Qwen/Qwen2.5-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct) on the [AlekseyKorshuk/ai-detection-gutenberg-human-v2-formatted-ai-sft](https://huggingface.co/datasets/AlekseyKorshuk/ai-detection-gutenberg-human-v2-formatted-ai-sft) dataset.
-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="AlekseyKorshuk/ai-detection-gutenberg-human-v2-formatted-ai-sft-qwen-7b-sft-3epochs", device="cuda")
-output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
-print(output["generated_text"])
-```
-
-## Training procedure
-
-[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="150" height="24"/>](https://wandb.ai/aleksey-korshuk/huggingface/runs/bfyzbjtg)
-
-This model was trained with SFT.
-
-### Framework versions
-
-- TRL: 0.12.0.dev0
-- Transformers: 4.46.0
-- Pytorch: 2.4.1+cu124
-- Datasets: 3.0.1
-- Tokenizers: 0.20.1
-
-## 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 Gallouédec},
-	year         = 2020,
-	journal      = {GitHub repository},
-	publisher    = {GitHub},
-	howpublished = {\url{https://github.com/huggingface/trl}}
-}
+---
+base_model: Qwen/Qwen2.5-7B-Instruct
+datasets: AlekseyKorshuk/ai-detection-gutenberg-human-v2-formatted-ai-sft
+library_name: transformers
+model_name: ai-detection-gutenberg-human-v2-formatted-ai-sft-qwen-7b-sft-3epochs
+tags:
+- generated_from_trainer
+- trl
+- sft
+licence: license
+language:
+- zho
+- eng
+- fra
+- spa
+- por
+- deu
+- ita
+- rus
+- jpn
+- kor
+- vie
+- tha
+- ara
+---
+
+# Model Card for ai-detection-gutenberg-human-v2-formatted-ai-sft-qwen-7b-sft-3epochs
+
+This model is a fine-tuned version of [Qwen/Qwen2.5-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct) on the [AlekseyKorshuk/ai-detection-gutenberg-human-v2-formatted-ai-sft](https://huggingface.co/datasets/AlekseyKorshuk/ai-detection-gutenberg-human-v2-formatted-ai-sft) dataset.
+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="AlekseyKorshuk/ai-detection-gutenberg-human-v2-formatted-ai-sft-qwen-7b-sft-3epochs", device="cuda")
+output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
+print(output["generated_text"])
+```
+
+## Training procedure
+
+[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="150" height="24"/>](https://wandb.ai/aleksey-korshuk/huggingface/runs/bfyzbjtg)
+
+This model was trained with SFT.
+
+### Framework versions
+
+- TRL: 0.12.0.dev0
+- Transformers: 4.46.0
+- Pytorch: 2.4.1+cu124
+- Datasets: 3.0.1
+- Tokenizers: 0.20.1
+
+## 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 Gallouédec},
+	year         = 2020,
+	journal      = {GitHub repository},
+	publisher    = {GitHub},
+	howpublished = {\url{https://github.com/huggingface/trl}}
+}
 ```