Update metadata with huggingface_hub (#1)

- Update metadata with huggingface_hub (909e0cfb914b7d85ba95fc242ecc89e5a2cd7ae3)

Co-authored-by: Vaibhav Srivastav <reach-vb@users.noreply.huggingface.co>

README.md

@@ -1,10 +1,11 @@
 ---
-license: apache-2.0
-license_link: https://huggingface.co/Qwen/Qwen2.5-14B-Instruct-AWQ/blob/main/LICENSE
+base_model: Qwen/Qwen2.5-14B-Instruct
 language:
 - en
+library_name: transformers
+license: apache-2.0
+license_link: https://huggingface.co/Qwen/Qwen2.5-14B-Instruct-AWQ/blob/main/LICENSE
 pipeline_tag: text-generation
-base_model: Qwen/Qwen2.5-14B-Instruct
 tags:
 - chat
 ---
@@ -49,8 +50,8 @@ Also check out our [AWQ documentation](https://qwen.readthedocs.io/en/latest/qua
 Here provides a code snippet with `apply_chat_template` to show you how to load the tokenizer and model and how to generate contents.
 
 ```python
-from modelscope import AutoModelForCausalLM, AutoTokenizer
-model_name = "qwen/Qwen2.5-14B-Instruct-AWQ"
+from transformers import AutoModelForCausalLM, AutoTokenizer
+model_name = "Qwen/Qwen2.5-14B-Instruct-AWQ"
 model = AutoModelForCausalLM.from_pretrained(
     model_name,
     torch_dtype="auto",
@@ -76,7 +77,6 @@ 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)
 ```
 
 ### Processing Long Texts