Improve language tag

README.md

@@ -1,95 +1,107 @@
----
-license: other
-license_name: tongyi-qianwen
-license_link: https://huggingface.co/Qwen/Qwen2-72B-Instruct/blob/main/LICENSE
-language:
-- en
-pipeline_tag: text-generation
-library_name: transformers
-tags:
-- mergekit
-- merge
-- lazymergekit
-base_model:
-- Qwen/Qwen2.5-72B-Instruct
----
-# BigQwen2.5-125B-Instruct
-
-![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/61b8e2ba285851687028d395/98GiKtmH1AtHHbIbOUH4Y.jpeg)
-
-BigQwen2.5-125B-Instruct is a [Qwen/Qwen2-72B-Instruct](https://huggingface.co/Qwen/Qwen2-72B-Instruct) self-merge made with [MergeKit](https://github.com/arcee-ai/mergekit/tree/main).
-
-It applies the [mlabonne/Meta-Llama-3-120B-Instruct](https://huggingface.co/mlabonne/Meta-Llama-3-120B-Instruct/) recipe.
-
-I made it due to popular demand but I haven't tested it so use it at your own risk. ¯\\\_(ツ)_/¯
-
-## 🔍 Applications
-
-It might be good for creative writing tasks. I recommend a context length of 32k but you can go up to 131,072 tokens in theory.
-
-## 🏆 Evaluation
-
-I think it's too big for the Open LLM Leaderboard, unfortunately. Here's some feedback from users (thanks a lot!):
-
-![image/png](https://cdn-uploads.huggingface.co/production/uploads/61b8e2ba285851687028d395/OhnwtXgIMIcr2pQqggXhU.png)
-
-![image/png](https://cdn-uploads.huggingface.co/production/uploads/61b8e2ba285851687028d395/8v_Eb6ZvpVYMhu8kMwklq.png)
-
-![image/png](https://cdn-uploads.huggingface.co/production/uploads/61b8e2ba285851687028d395/Px4f-BTJ8nDihzPJ0F47K.png)
-
-## 🧩 Configuration
-
-The following YAML configuration was used to produce this model:
-
-```yaml
-slices:
-- sources:
-  - layer_range: [0, 20]
-    model: Qwen/Qwen2.5-72B-Instruct
-- sources:
-  - layer_range: [10, 30]
-    model: Qwen/Qwen2.5-72B-Instruct
-- sources:
-  - layer_range: [20, 40]
-    model: Qwen/Qwen2.5-72B-Instruct
-- sources:
-  - layer_range: [30, 50]
-    model: Qwen/Qwen2.5-72B-Instruct
-- sources:
-  - layer_range: [40, 60]
-    model: Qwen/Qwen2.5-72B-Instruct
-- sources:
-  - layer_range: [50, 70]
-    model: Qwen/Qwen2.5-72B-Instruct
-- sources:
-  - layer_range: [60, 80]
-    model: Qwen/Qwen2.5-72B-Instruct
-merge_method: passthrough
-dtype: bfloat16
-
-```
-
-## 💻 Usage
-
-```python
-!pip install -qU transformers accelerate
-
-from transformers import AutoTokenizer
-import transformers
-import torch
-
-model = "mlabonne/BigQwen2.5-125B-Instruct"
-messages = [{"role": "user", "content": "What is a large language model?"}]
-
-tokenizer = AutoTokenizer.from_pretrained(model)
-prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
-pipeline = transformers.pipeline(
-    "text-generation",
-    model=model,
-    torch_dtype=torch.float16,
-    device_map="auto",
-)
-
-outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
-print(outputs[0]["generated_text"])
+---
+license: other
+license_name: tongyi-qianwen
+license_link: https://huggingface.co/Qwen/Qwen2-72B-Instruct/blob/main/LICENSE
+language:
+- zho
+- eng
+- fra
+- spa
+- por
+- deu
+- ita
+- rus
+- jpn
+- kor
+- vie
+- tha
+- ara
+pipeline_tag: text-generation
+library_name: transformers
+tags:
+- mergekit
+- merge
+- lazymergekit
+base_model:
+- Qwen/Qwen2.5-72B-Instruct
+---
+# BigQwen2.5-125B-Instruct
+
+![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/61b8e2ba285851687028d395/98GiKtmH1AtHHbIbOUH4Y.jpeg)
+
+BigQwen2.5-125B-Instruct is a [Qwen/Qwen2-72B-Instruct](https://huggingface.co/Qwen/Qwen2-72B-Instruct) self-merge made with [MergeKit](https://github.com/arcee-ai/mergekit/tree/main).
+
+It applies the [mlabonne/Meta-Llama-3-120B-Instruct](https://huggingface.co/mlabonne/Meta-Llama-3-120B-Instruct/) recipe.
+
+I made it due to popular demand but I haven't tested it so use it at your own risk. ¯\\\_(ツ)_/¯
+
+## 🔍 Applications
+
+It might be good for creative writing tasks. I recommend a context length of 32k but you can go up to 131,072 tokens in theory.
+
+## 🏆 Evaluation
+
+I think it's too big for the Open LLM Leaderboard, unfortunately. Here's some feedback from users (thanks a lot!):
+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/61b8e2ba285851687028d395/OhnwtXgIMIcr2pQqggXhU.png)
+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/61b8e2ba285851687028d395/8v_Eb6ZvpVYMhu8kMwklq.png)
+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/61b8e2ba285851687028d395/Px4f-BTJ8nDihzPJ0F47K.png)
+
+## 🧩 Configuration
+
+The following YAML configuration was used to produce this model:
+
+```yaml
+slices:
+- sources:
+  - layer_range: [0, 20]
+    model: Qwen/Qwen2.5-72B-Instruct
+- sources:
+  - layer_range: [10, 30]
+    model: Qwen/Qwen2.5-72B-Instruct
+- sources:
+  - layer_range: [20, 40]
+    model: Qwen/Qwen2.5-72B-Instruct
+- sources:
+  - layer_range: [30, 50]
+    model: Qwen/Qwen2.5-72B-Instruct
+- sources:
+  - layer_range: [40, 60]
+    model: Qwen/Qwen2.5-72B-Instruct
+- sources:
+  - layer_range: [50, 70]
+    model: Qwen/Qwen2.5-72B-Instruct
+- sources:
+  - layer_range: [60, 80]
+    model: Qwen/Qwen2.5-72B-Instruct
+merge_method: passthrough
+dtype: bfloat16
+
+```
+
+## 💻 Usage
+
+```python
+!pip install -qU transformers accelerate
+
+from transformers import AutoTokenizer
+import transformers
+import torch
+
+model = "mlabonne/BigQwen2.5-125B-Instruct"
+messages = [{"role": "user", "content": "What is a large language model?"}]
+
+tokenizer = AutoTokenizer.from_pretrained(model)
+prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+pipeline = transformers.pipeline(
+    "text-generation",
+    model=model,
+    torch_dtype=torch.float16,
+    device_map="auto",
+)
+
+outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
+print(outputs[0]["generated_text"])
 ```