panagoa
/

nllb-200-based-kbd-morphologizer

@@ -1,199 +1,68 @@
 ---
 library_name: transformers
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 ---
 library_name: transformers
+language:
+- kbd
+base_model:
+- panagoa/nllb-200-distilled-600M-kbd-v0.1
+pipeline_tag: text2text-generation
 ---
+```python
+def word_to_morph_features(text):
+    prefix = "<word analyze>: "
+    inputs = tokenizer(prefix + text, return_tensors="pt", max_length=128, truncation=True)
+    device = model.device
+    inputs = {k: v.to(device) for k, v in inputs.items()}
+    outputs = model.generate(**inputs)
+    return tokenizer.decode(outputs[0], skip_special_tokens=True)
+test_words = [
+  'зезгъэщхьырт',
+  'псыхьыжауэ',
+  'хъужами',
+  'япыщIат',
+  'къыщежьэри',
+  'схъумэрт',
+  'щхьэпэщ',
+  'сылъакъуэ',
+  'къеджэмэ',
+  'гъэщам',
+  'бэракъыу',
+  'уеупщIакъым',
+  'къэзыгъэпэж',
+  'къахуэбла',
+  'иращIэнтэкъым',
+  'къыбоух',
+  'гъусари',
+  'сщитIэгъащ',
+  'дытелажьэу',
+]
+for word in test_words:
+    features = word_to_morph_features(word)
+    print(f"{word} -> {features}")
+```
+```text
+зезгъэщхьырт -> <features>: 1sg-pre-1sg-caus-know-past
+псыхьыжауэ -> <features>: water-water-adv
+хъужами -> <features>: become-past-conn
+япыщIат -> <features>: 3pl-attach-past-aff
+къыщежьэри -> <features>: hor-begin-and
+схъумэрт -> <features>: 1sg-caus-stand-epv-fut
+щхьэпэщ -> <features>: dir-ben-val-aff
+сылъакъуэ -> <features>: 1sg-run-adv
+къеджэмэ -> <features>: hor-read-cond
+гъэщам -> <features>: year-erg
+бэракъыу -> <features>: flag-adv
+уеупщIакъым -> <features>: 2sg-ben-ask-neg
+къэзыгъэпэж -> <features>: hor-rel-caus-caus-run-back
+къахуэбла -> <features>: hor-ben-loc-approach
+иращIэнтэкъым -> <features>: 3pl-ben-3pl-do-epv-fut-neg
+къыбоух -> <features>: 2sg-dir-2sg-caus-fall
+гъусари -> <features>: companion-and
+сщитIэгъащ -> <features>: 1sg-ben-1sg-put-past
+дытелажьэу -> <features>: 1pl-dir-work-adv
+```