Create README.md

README.md

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+---
+license: mit
+datasets:
+- uvci/Koumankan_mt_dyu_fr
+language:
+- fr
+metrics:
+- bleu
+- chrf
+library_name: adapter-transformers
+pipeline_tag: translation
+---
+
+# Adeptschneider/dyu-fr-joeynmt
+
+A machine translation model that translates Dyula to French using the [JoeyNMT framework](https://github.com/joeynmt/joeynmt).
+
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Usage
+
+### Load and use for inference
+
+```python
+import torch
+from joeynmt.config import load_config, parse_global_args
+from joeynmt.prediction import predict, prepare
+from huggingface_hub import snapshot_download
+
+# Download model
+snapshot_download(
+    repo_id="Adeptschneider/joeynmt-dyu-fr-v19.0",
+    local_dir="/path/to/save/locally"
+)
+
+# Define model interface
+class JoeyNMTModel:
+    '''
+    JoeyNMTModel which load JoeyNMT model for inference.
+
+    :param config_path: Path to YAML config file
+    :param n_best: return this many hypotheses, <= beam (currently only 1)
+    '''
+    def __init__(self, config_path: str, n_best: int = 1):
+        seed = 42
+        torch.manual_seed(seed)
+        cfg = load_config(config_path)
+        args = parse_global_args(cfg, rank=0, mode="translate")
+        self.args = args._replace(test=args.test._replace(n_best=n_best))
+        # build model
+        self.model, _, _, self.test_data = prepare(self.args, rank=0, mode="translate")
+
+    def _translate_data(self):
+        _, _, hypotheses, trg_tokens, trg_scores, _ = predict(
+            model=self.model,
+            data=self.test_data,
+            compute_loss=False,
+            device=self.args.device,
+            rank=0,
+            n_gpu=self.args.n_gpu,
+            normalization="none",
+            num_workers=self.args.num_workers,
+            args=self.args.test,
+            autocast=self.args.autocast,
+        )
+        return hypotheses, trg_tokens, trg_scores
+
+    def translate(self, sentence) -> list:
+        '''
+        Translate the given sentence.
+
+        :param sentence: Sentence to be translated
+        :return:
+        - translations: (list of str) possible translations of the sentence.
+        '''
+        self.test_data.set_item(sentence.strip())
+        translations, _, _ = self._translate_data()
+        assert len(translations) == len(self.test_data) * self.args.test.n_best
+        self.test_data.reset_cache()
+        return translations
+
+# Load model
+config_path = "/path/to/lean_model/config_local.yaml" # Change this to the path to your model congig file
+model = JoeyNMTModel(config_path=config_path, n_best=1)
+
+# Translate
+model.translate(sentence="i tɔgɔ bi cogodɔ")
+```
+
+## Training procedure
+
+### Training hyperparameters
+
+More information needed
+
+### Training results
+
+More information needed
+
+### Framework versions
+
+- JoeyNMT 2.3.0
+- Torch 2.0.1+cu118