Improve language tag

Hi! As the model is multilingual, this is a PR to add other languages than English to the language tag to improve the referencing. Note that 29 languages are announced in the README, but only 13 are explicitly listed. I was therefore only able to add these 13 languages.

README.md

@@ -1,48 +1,60 @@
----
-base_model: Qwen/Qwen2.5-7B-Instruct
-library_name: peft
-license: apache-2.0
-datasets:
-- medalpaca/medical_meadow_medical_flashcards
-language:
-- en
-pipeline_tag: text-generation
----
-
-# Model Card for FlowerTune-Qwen2.5-7B-Instruct-Medical-PEFT
-
-This PEFT adapter has been trained by using [Flower](https://flower.ai/), a friendly federated AI framework.
-
-The adapter and benchmark results have been submitted to the [FlowerTune LLM Medical Leaderboard](https://flower.ai/benchmarks/llm-leaderboard/medical/).
-
-
-## Model Details
-
-Please check the following GitHub project for model details and evaluation results:
-
-[https://github.com/mrs83/FlowerTune-Qwen2.5-7B-Instruct-Medical](https://github.com/mrs83/FlowerTune-Qwen2.5-7B-Instruct-Medical)
-
-
-## Training procedure
-
-
-The following `bitsandbytes` quantization config was used during training:
-- quant_method: bitsandbytes
-- _load_in_8bit: False
-- _load_in_4bit: True
-- llm_int8_threshold: 6.0
-- llm_int8_skip_modules: None
-- llm_int8_enable_fp32_cpu_offload: False
-- llm_int8_has_fp16_weight: False
-- bnb_4bit_quant_type: fp4
-- bnb_4bit_use_double_quant: False
-- bnb_4bit_compute_dtype: float32
-- bnb_4bit_quant_storage: uint8
-- load_in_4bit: True
-- load_in_8bit: False
-
-### Framework versions
-
-
-- PEFT 0.6.2
+---
+base_model: Qwen/Qwen2.5-7B-Instruct
+library_name: peft
+license: apache-2.0
+datasets:
+- medalpaca/medical_meadow_medical_flashcards
+language:
+- zho
+- eng
+- fra
+- spa
+- por
+- deu
+- ita
+- rus
+- jpn
+- kor
+- vie
+- tha
+- ara
+pipeline_tag: text-generation
+---
+
+# Model Card for FlowerTune-Qwen2.5-7B-Instruct-Medical-PEFT
+
+This PEFT adapter has been trained by using [Flower](https://flower.ai/), a friendly federated AI framework.
+
+The adapter and benchmark results have been submitted to the [FlowerTune LLM Medical Leaderboard](https://flower.ai/benchmarks/llm-leaderboard/medical/).
+
+
+## Model Details
+
+Please check the following GitHub project for model details and evaluation results:
+
+[https://github.com/mrs83/FlowerTune-Qwen2.5-7B-Instruct-Medical](https://github.com/mrs83/FlowerTune-Qwen2.5-7B-Instruct-Medical)
+
+
+## Training procedure
+
+
+The following `bitsandbytes` quantization config was used during training:
+- quant_method: bitsandbytes
+- _load_in_8bit: False
+- _load_in_4bit: True
+- llm_int8_threshold: 6.0
+- llm_int8_skip_modules: None
+- llm_int8_enable_fp32_cpu_offload: False
+- llm_int8_has_fp16_weight: False
+- bnb_4bit_quant_type: fp4
+- bnb_4bit_use_double_quant: False
+- bnb_4bit_compute_dtype: float32
+- bnb_4bit_quant_storage: uint8
+- load_in_4bit: True
+- load_in_8bit: False
+
+### Framework versions
+
+
+- PEFT 0.6.2
 - Flower 1.12.0