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

@@ -1,99 +1,111 @@
----
-license: apache-2.0
-language:
-- en
-base_model:
-- Qwen/Qwen2.5-3B-Instruct
-pipeline_tag: text-generation
-library_name: transformers
----
-
-# Qwen-2.5-3B-Instruct-ov-INT8 
-* Model creator: [Qwen](https://huggingface.co/Qwen)
- * Original model: [Qwen2.5-3B-Instruct](https://huggingface.co/Qwen/Qwen2.5-3B-Instruct)
-
-## Description
-This is [Qwen2.5-3B-Instruct](https://huggingface.co/Qwen/Qwen2.5-3B-Instruct) model converted to the [OpenVINO™ IR](https://docs.openvino.ai/2024/documentation/openvino-ir-format.html) (Intermediate Representation) format with weights compressed to INT8 by [NNCF](https://github.com/openvinotoolkit/nncf).
-
-## Quantization Parameters
-
-Weight compression was performed using `nncf.compress_weights` with the following parameters:
-
-* mode: **int8_asym**
-* ratio: **0.8**
-* group_size: **128**
-
-For more information on quantization, check the [OpenVINO model optimization guide](https://docs.openvino.ai/2024/openvino-workflow/model-optimization-guide/weight-compression.html).
-
-
-## Compatibility
-
-The provided OpenVINO™ IR model is compatible with:
-
-* OpenVINO version 2024.4.0 and higher
-* Optimum Intel 1.19.0 and higher
-
-## Prompt Template
-
-```
-<|im_start|>system
-You are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>
-<|im_start|>user
-{input}<|im_end|>
-```
-
-## Running Model Inference with [Optimum Intel](https://huggingface.co/docs/optimum/intel/index)
-
-
-1. Install packages required for using [Optimum Intel](https://huggingface.co/docs/optimum/intel/index) integration with the OpenVINO backend:
-
-```
-pip install optimum[openvino]
-```
-
-2. Run model inference:
-
-```
-from transformers import AutoTokenizer
-from optimum.intel.openvino import OVModelForCausalLM
-
-model_id = "srang992/Qwen-2.5-3B-Instruct-ov-INT8"
-tokenizer = AutoTokenizer.from_pretrained(model_id)
-model = OVModelForCausalLM.from_pretrained(model_id)
-
-inputs = tokenizer("What is OpenVINO?", return_tensors="pt")
-
-outputs = model.generate(**inputs, max_length=200)
-text = tokenizer.batch_decode(outputs)[0]
-print(text)
-```
-
-For more examples and possible optimizations, refer to the [OpenVINO Large Language Model Inference Guide](https://docs.openvino.ai/2024/learn-openvino/llm_inference_guide.html).
-
-## Running Model Inference with [OpenVINO GenAI](https://github.com/openvinotoolkit/openvino.genai)
-
-1. Install packages required for using OpenVINO GenAI.
-```
-pip install openvino-genai huggingface_hub
-```
-
-2. Download model from HuggingFace Hub
-   
-```
-import huggingface_hub as hf_hub
-
-model_id = "srang992/Qwen-2.5-3B-Instruct-ov-INT8"
-model_path = "Qwen-2.5-3B-Instruct-ov-INT8"
-
-hf_hub.snapshot_download(model_id, local_dir=model_path)
-
-```
-
-3. Run model inference:
-
-```
-import openvino_genai as ov_genai
-
-device = "CPU"
-pipe = ov_genai.LLMPipeline(model_path, device)
+---
+license: apache-2.0
+language:
+- zho
+- eng
+- fra
+- spa
+- por
+- deu
+- ita
+- rus
+- jpn
+- kor
+- vie
+- tha
+- ara
+base_model:
+- Qwen/Qwen2.5-3B-Instruct
+pipeline_tag: text-generation
+library_name: transformers
+---
+
+# Qwen-2.5-3B-Instruct-ov-INT8 
+* Model creator: [Qwen](https://huggingface.co/Qwen)
+ * Original model: [Qwen2.5-3B-Instruct](https://huggingface.co/Qwen/Qwen2.5-3B-Instruct)
+
+## Description
+This is [Qwen2.5-3B-Instruct](https://huggingface.co/Qwen/Qwen2.5-3B-Instruct) model converted to the [OpenVINO™ IR](https://docs.openvino.ai/2024/documentation/openvino-ir-format.html) (Intermediate Representation) format with weights compressed to INT8 by [NNCF](https://github.com/openvinotoolkit/nncf).
+
+## Quantization Parameters
+
+Weight compression was performed using `nncf.compress_weights` with the following parameters:
+
+* mode: **int8_asym**
+* ratio: **0.8**
+* group_size: **128**
+
+For more information on quantization, check the [OpenVINO model optimization guide](https://docs.openvino.ai/2024/openvino-workflow/model-optimization-guide/weight-compression.html).
+
+
+## Compatibility
+
+The provided OpenVINO™ IR model is compatible with:
+
+* OpenVINO version 2024.4.0 and higher
+* Optimum Intel 1.19.0 and higher
+
+## Prompt Template
+
+```
+<|im_start|>system
+You are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>
+<|im_start|>user
+{input}<|im_end|>
+```
+
+## Running Model Inference with [Optimum Intel](https://huggingface.co/docs/optimum/intel/index)
+
+
+1. Install packages required for using [Optimum Intel](https://huggingface.co/docs/optimum/intel/index) integration with the OpenVINO backend:
+
+```
+pip install optimum[openvino]
+```
+
+2. Run model inference:
+
+```
+from transformers import AutoTokenizer
+from optimum.intel.openvino import OVModelForCausalLM
+
+model_id = "srang992/Qwen-2.5-3B-Instruct-ov-INT8"
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = OVModelForCausalLM.from_pretrained(model_id)
+
+inputs = tokenizer("What is OpenVINO?", return_tensors="pt")
+
+outputs = model.generate(**inputs, max_length=200)
+text = tokenizer.batch_decode(outputs)[0]
+print(text)
+```
+
+For more examples and possible optimizations, refer to the [OpenVINO Large Language Model Inference Guide](https://docs.openvino.ai/2024/learn-openvino/llm_inference_guide.html).
+
+## Running Model Inference with [OpenVINO GenAI](https://github.com/openvinotoolkit/openvino.genai)
+
+1. Install packages required for using OpenVINO GenAI.
+```
+pip install openvino-genai huggingface_hub
+```
+
+2. Download model from HuggingFace Hub
+   
+```
+import huggingface_hub as hf_hub
+
+model_id = "srang992/Qwen-2.5-3B-Instruct-ov-INT8"
+model_path = "Qwen-2.5-3B-Instruct-ov-INT8"
+
+hf_hub.snapshot_download(model_id, local_dir=model_path)
+
+```
+
+3. Run model inference:
+
+```
+import openvino_genai as ov_genai
+
+device = "CPU"
+pipe = ov_genai.LLMPipeline(model_path, device)
 print(pipe.generate("What is OpenVINO?", max_length=200))