Create README.md

README.md

@@ -0,0 +1,46 @@
+---
+license: mit
+widget:
+- text: |-
+    <SC1>- как ты?
+    - <extra_id_0>
+  example_title: how r u
+language:
+- ru
+tags:
+- conversational
+---
+
+How to use:
+
+```python
+import torch
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+
+device='cuda'
+tokenizer = AutoTokenizer.from_pretrained('TeraSpace/dialofrednocontext_V2')
+model = AutoModelForSeq2SeqLM.from_pretrained('TeraSpace/dialofrednocontext_V2').to(device)
+while True:
+    text_inp = input("=>")
+    lm_text=f'<SC1>- {text_inp}\n- <extra_id_0>'
+    input_ids=torch.tensor([tokenizer.encode(lm_text)]).to(device)
+    # outputs=model.generate(input_ids=input_ids,
+    #                                 max_length=200,
+    #                                 eos_token_id=tokenizer.eos_token_id,
+    #                                 early_stopping=True,
+    #                                 do_sample=True,
+    #                                 temperature=1.0,
+    #                                 top_k=0,
+    #                                 top_p=0.85)
+    # outputs=model.generate(input_ids,eos_token_id=tokenizer.eos_token_id,early_stopping=True)
+    outputs=model.generate(input_ids=input_ids,
+                                    max_length=200,
+                                    eos_token_id=tokenizer.eos_token_id,
+                                    early_stopping=True,
+                                    do_sample=True,
+                                    temperature=0.7,
+                                    top_k=0,
+                                    top_p=0.8)
+    
+    print(tokenizer.decode(outputs[0][1:]))
+```