Update README.md

README.md

@@ -32,6 +32,52 @@ CTranslate2 is one of the most performant ways of hosting translation models at
 
 The project is production-oriented and comes with backward compatibility guarantees, but it also includes experimental features related to model compression and inference acceleration.
 
+# CTranslate2 Installation
+```bash
+pip install hf-hub-ctranslate2>=1.0.0 ctranslate2>=3.13.0
+```
+### ct2-transformers-converter Command Used:
+```bash
+ct2-transformers-converter --model Helsinki-NLP/opus-mt-cau-en --output_dir ./ctranslate2/opus-mt-cau-en-ctranslate2 --force --copy_files README.md generation_config.json tokenizer_config.json vocab.json source.spm .gitattributes target.spm --quantization float16
+```
+# CTranslate2 Converted Checkpoint Information:
+**Compatible With:**
+- [ctranslate2](https://github.com/OpenNMT/CTranslate2)
+- [hf-hub-ctranslate2](https://github.com/michaelfeil/hf-hub-ctranslate2)
+
+**Compute Type:**
+- `compute_type=int8_float16` for `device="cuda"`
+- `compute_type=int8`  for `device="cpu"`
+
+# Sample Code - ctranslate2
+#### Clone the repository to the working directory or wherever you wish to store the model artifacts. ####
+```bash
+git clone https://huggingface.co/gaudi/opus-mt-cau-en-ctranslate2
+```
+
+#### Take the python code below and update the 'model_dir' variable to the location of the cloned repository. ####
+
+```python
+from ctranslate2 import Translator
+import transformers
+
+model_dir = "./mt-hitz-en-eu-ct2" # Path to model directory.
+translator = Translator(
+            model_path=model_dir,
+            device="cuda", # cpu, cuda, or auto.
+            inter_threads=1, # Maximum number of parallel translations.
+            intra_threads=4, # Number of OpenMP threads per translator.
+            compute_type="int8_float16", # int8 for cpu or int8_float16 for cuda.
+)
+
+tokenizer = transformers.AutoTokenizer.from_pretrained(model_dir)
+
+source = tokenizer.convert_ids_to_tokens(tokenizer.encode("Hello, world!"))
+results = translator.translate_batch([source])
+target = results[0].hypotheses[0]
+
+print(tokenizer.decode(tokenizer.convert_tokens_to_ids(target)))
+```
 
 ### Licensing information
 This work is licensed under a [Apache License, Version 2.0](https://www.apache.org/licenses/LICENSE-2.0)