Improve language tag

README.md

@@ -1,50 +1,62 @@
----
-license: cc
-language:
-- en
-base_model:
-- Qwen/Qwen2.5-1.5B-Instruct
----
-
-todos:
-* check numerical output same as original VILA impl
-* check training stablitiy
-* save_pretrained()
-
-already finished
-* AutoModel.from_pretrained() / device_map auto to shard
-* loading 
-* fix recursive imports
-* text conv 
-* image + text conv: 
-    * .generate() / .generate_content()
-    * llava/cli/infer.py
-    * tests/bash/test_inference.sh
-
-## NVILA HF Comptatible Mode
-Remote model loading example 
-
-```python
-from transformers import AutoConfig, AutoModel
-from termcolor import colored
-
-model_path = "Efficient-Large-Model/nvila_lite_3b_dev"
-print("main_dev.py, loading from ", model_path)
-
-# config = AutoConfig.from_pretrained(model_path, trust_remote_code=True)
-# model = AutoModel.from_config(config, trust_remote_code=True)
-model = AutoModel.from_pretrained(model_path, trust_remote_code=True, device_map="auto")
-res = model.generate_content([
-    "how are you today?"
-])
-print(colored(res, "cyan", attrs=["bold"]))
-
-print("---" * 40)
-
-import PIL.Image
-response = model.generate_content([
-    PIL.Image.open("inference_test/test_data/caption_meat.jpeg"),
-    "describe the image?"
-])
-print(colored(response, "cyan", attrs=["bold"]))
+---
+license: cc
+language:
+- zho
+- eng
+- fra
+- spa
+- por
+- deu
+- ita
+- rus
+- jpn
+- kor
+- vie
+- tha
+- ara
+base_model:
+- Qwen/Qwen2.5-1.5B-Instruct
+---
+
+todos:
+* check numerical output same as original VILA impl
+* check training stablitiy
+* save_pretrained()
+
+already finished
+* AutoModel.from_pretrained() / device_map auto to shard
+* loading 
+* fix recursive imports
+* text conv 
+* image + text conv: 
+    * .generate() / .generate_content()
+    * llava/cli/infer.py
+    * tests/bash/test_inference.sh
+
+## NVILA HF Comptatible Mode
+Remote model loading example 
+
+```python
+from transformers import AutoConfig, AutoModel
+from termcolor import colored
+
+model_path = "Efficient-Large-Model/nvila_lite_3b_dev"
+print("main_dev.py, loading from ", model_path)
+
+# config = AutoConfig.from_pretrained(model_path, trust_remote_code=True)
+# model = AutoModel.from_config(config, trust_remote_code=True)
+model = AutoModel.from_pretrained(model_path, trust_remote_code=True, device_map="auto")
+res = model.generate_content([
+    "how are you today?"
+])
+print(colored(res, "cyan", attrs=["bold"]))
+
+print("---" * 40)
+
+import PIL.Image
+response = model.generate_content([
+    PIL.Image.open("inference_test/test_data/caption_meat.jpeg"),
+    "describe the image?"
+])
+print(colored(response, "cyan", attrs=["bold"]))
 ```