Improve Model Card: Update pipeline_tag, add library_name, and correct language tag

This PR enhances the model card by:

* **Updating the `pipeline_tag`**: Changed from `translation` to `text-generation`. While the model is used for translation, it functions as a large language model (LLM) for text generation, making `text-generation` a more accurate and discoverable primary pipeline tag on the Hugging Face Hub.
* **Adding `library_name`**: Added `library_name: transformers` to the metadata. Evidence from the `Quickstart` code snippet (using `transformers.AutoModelForCausalLM` and `AutoTokenizer`) confirms compatibility with the Hugging Face Transformers library, enabling the automated "how to use" widget.
* **Correcting `language` tag**: Corrected `false` to `no` (Norwegian) in the `language` metadata, aligning with the "Support Languages" table in the model card and GitHub README, which lists Norwegian as a supported language.

These changes improve the model's discoverability and usability for users.

README.md

@@ -1,4 +1,6 @@
 ---
+base_model:
+- Qwen/Qwen3-4B-Base
 language:
 - en
 - zh
@@ -60,10 +62,9 @@ language:
 - ur
 - uz
 - yue
-base_model:
-- Qwen/Qwen3-4B-Base
 license: apache-2.0
-pipeline_tag: translation
+pipeline_tag: text-generation
+library_name: transformers
 ---
 
 ## LMT
@@ -95,7 +96,9 @@ model_name = "NiuTrans/LMT-60-8B"
 tokenizer = AutoTokenizer.from_pretrained(model_name, padding_side='left')
 model = AutoModelForCausalLM.from_pretrained(model_name)
 
-prompt = "Translate the following text from English into Chinese.\nEnglish: The concept came from China where plum blossoms were the flower of choice.\nChinese: "
+prompt = "Translate the following text from English into Chinese.
+English: The concept came from China where plum blossoms were the flower of choice.
+Chinese: "
 messages = [{"role": "user", "content": prompt}]
 text = tokenizer.apply_chat_template(
     messages,