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

@@ -1,67 +1,79 @@
----
-license: mit
-language:
-- en
-base_model:
-- Qwen/Qwen2.5-32B-Instruct
-pipeline_tag: text-generation
----
-
-# Apollo Model
-
-This is an experimental hybrid reasoning model built on Qwen2.5-32B-Instruct
-
-# GGUF
-
-mradermacher/Apollo-v3-32B-GGUF
-
-thanks mradermacher for this gguf
-
-### Merge Method
-
-This model was merged using the [Model Stock](https://arxiv.org/abs/2403.19522) merge method using [Qwen/Qwen2.5-32B-Instruct](https://huggingface.co/Qwen/Qwen2.5-32B-Instruct) as a base.
-
-
-### Enable reasoning
-
-prompt the LLM with think deeper and step by step
-
-### Example code 
-
-```
-
-from transformers import AutoModelForCausalLM, AutoTokenizer
-
-model_name = "rootxhacker/Apollo-v3-32B"
-
-model = AutoModelForCausalLM.from_pretrained(
-model_name,
-torch_dtype="auto",
-device_map="auto"
-)
-tokenizer = AutoTokenizer.from_pretrained(model_name)
-
-prompt = "How many r's are in the word strawberry"
-messages = [
-{"role": "user", "content": prompt}
-]
-text = tokenizer.apply_chat_template(
-messages,
-tokenize=False,
-add_generation_prompt=True
-)
-
-model_inputs = tokenizer([text], return_tensors="pt").to(model.device)
-
-generated_ids = model.generate(
-**model_inputs,
-max_new_tokens=32768
-)
-generated_ids = [
-output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)
-]
-
-response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
-print(response)
-
+---
+license: mit
+language:
+- zho
+- eng
+- fra
+- spa
+- por
+- deu
+- ita
+- rus
+- jpn
+- kor
+- vie
+- tha
+- ara
+base_model:
+- Qwen/Qwen2.5-32B-Instruct
+pipeline_tag: text-generation
+---
+
+# Apollo Model
+
+This is an experimental hybrid reasoning model built on Qwen2.5-32B-Instruct
+
+# GGUF
+
+mradermacher/Apollo-v3-32B-GGUF
+
+thanks mradermacher for this gguf
+
+### Merge Method
+
+This model was merged using the [Model Stock](https://arxiv.org/abs/2403.19522) merge method using [Qwen/Qwen2.5-32B-Instruct](https://huggingface.co/Qwen/Qwen2.5-32B-Instruct) as a base.
+
+
+### Enable reasoning
+
+prompt the LLM with think deeper and step by step
+
+### Example code 
+
+```
+
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model_name = "rootxhacker/Apollo-v3-32B"
+
+model = AutoModelForCausalLM.from_pretrained(
+model_name,
+torch_dtype="auto",
+device_map="auto"
+)
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+
+prompt = "How many r's are in the word strawberry"
+messages = [
+{"role": "user", "content": prompt}
+]
+text = tokenizer.apply_chat_template(
+messages,
+tokenize=False,
+add_generation_prompt=True
+)
+
+model_inputs = tokenizer([text], return_tensors="pt").to(model.device)
+
+generated_ids = model.generate(
+**model_inputs,
+max_new_tokens=32768
+)
+generated_ids = [
+output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)
+]
+
+response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
+print(response)
+
 ```