write README.md refering to cifope/nllb-200-wo-fr-distilled-600M

README.md

@@ -1,3 +1,52 @@
----
-license: cc-by-nc-4.0
----
+---
+license: cc-by-nc-4.0
+language:
+- en
+- zh
+metrics:
+- bleu
+pipeline_tag: translation
+---
+
+# Model Documentation: English to Simplified Chinese Translation with NLLB-200-distilled-600M
+
+## Model Overview
+
+This document describes a machine translation model fine-tuned from Meta's NLLB-200-distilled-600M for translating from English to Simplified Chinese. The model, hosted at `HackerMonica/nllb-200-distilled-600M-en-zh_CN`, utilizes a distilled version of the NLLB-200 model which has been specifically optimized for translation tasks between the English and Simplified Chinese languages.
+
+## Dependencies
+
+The model requires the `transformers` library by Hugging Face. Ensure that you have the library installed:
+
+```bash
+pip install transformers
+```
+
+## Setup
+
+Import necessary classes from the `transformers` library:
+
+```python
+from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
+```
+
+Initialize the model and tokenizer:
+
+```python
+model = AutoModelForSeq2SeqLM.from_pretrained('HackerMonica/nllb-200-distilled-600M-en-zh_CN')
+tokenizer = AutoTokenizer.from_pretrained('HackerMonica/nllb-200-distilled-600M-en-zh_CN')
+```
+
+## Usage
+
+To use the model for translating text, use python code below to translate text from English to Simplified Chinese:
+
+```python
+def translate(text):
+    inputs = tokenizer(text, return_tensors="pt").to("cuda")
+    translated_tokens = model.generate(
+        **inputs, forced_bos_token_id=tokenizer.lang_code_to_id["zho_Hans"], max_length=300
+    )
+    translation = tokenizer.batch_decode(translated_tokens, skip_special_tokens=True)[0]
+    return translation
+```