Create README.md

README.md

@@ -0,0 +1,54 @@
+---
+license: apache-2.0
+datasets:
+- artemsnegirev/ru-word-games
+language:
+- ru
+metrics:
+- exact_match
+pipeline_tag: text2text-generation
+---
+
+Model was trained on companion [dataset](artemsnegirev/ru-word-games). Minibob guess word from a description modeling well known Alias word game.
+
+```python
+from transformers import T5ForConditionalGeneration, T5Tokenizer
+
+prefix = "guess word:"
+
+def predict_word(prompt, model, tokenizer):
+ prompt = prompt.replace("...", "<extra_id_0>")
+ prompt = f"{prefix} {prompt}"
+
+ input_ids = tokenizer([prompt], return_tensors="pt").input_ids
+
+ outputs = model.generate(
+ input_ids.to(model.device), 
+ num_beams=5, 
+ max_new_tokens=8,
+ do_sample=False,
+ num_return_sequences=5
+ )
+
+ candidates = set()
+ 
+ for tokens in outputs:
+ candidate = tokenizer.decode(tokens, skip_special_tokens=True)
+ candidate = candidate.strip().lower()
+
+ candidates.add(candidate)
+
+ return candidates
+
+model_name = "artemsnegirev/minibob"
+
+tokenizer = T5Tokenizer.from_pretrained(model_name)
+model = T5ForConditionalGeneration.from_pretrained(model_name)
+
+prompt = "это животное с копытами на нем ездят"
+
+print(predict_word(prompt, model, tokenizer))
+# {'верблюд', 'конь', 'коня', 'лошадь', 'пони'}
+```
+
+Detailed github-based [tutorial](https://github.com/artemsnegirev/minibob) with pipeline and source code for building Minibob