初始化项目，由ModelHub XC社区提供模型

Model: Vikhrmodels/it-5.2-fp16-cp
Source: Original Platform

README.md

@@ -0,0 +1,59 @@
+---
+library_name: transformers
+language:
+- ru
+- en
+license: apache-2.0
+---
+
+# Релиз вихря 0.5
+
+Долили сильно больше данных в sft, теперь стабильнее работает json и multiturn, слегка подточили параметры претрена модели
+
+Added a lot more data to sft, now json and multiturn work more stable on long context and hard prompts
+
+ - [Google Colab](https://colab.research.google.com/drive/1-_BWsJycBm3rEyjpBx2_ejshpemQYHbe?usp=sharing)
+ - [GGUF](https://huggingface.co/Vikhrmodels/it-5.2-fp16-cp-GGUF)
+
+```python
+
+
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import torch
+model = AutoModelForCausalLM.from_pretrained("Vikhrmodels/it-5.2-fp16-cp",
+                                             device_map="auto",
+                                             attn_implementation="sdpa",
+                                             torch_dtype=torch.bfloat16)
+
+tokenizer = AutoTokenizer.from_pretrained("Vikhrmodels/it-5.2-fp16-cp")
+from transformers import  AutoTokenizer, pipeline
+pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)
+prompts = [
+    "В чем разница между фруктом и овощем?",
+    "Годы жизни колмагорова?"]
+
+def test_inference(prompt):
+    prompt = pipe.tokenizer.apply_chat_template([{"role": "user", "content": prompt}], tokenize=False, add_generation_prompt=True)
+    print(prompt)
+    outputs = pipe(prompt, max_new_tokens=512, do_sample=True, num_beams=1, temperature=0.25, top_k=50, top_p=0.98, eos_token_id=79097)
+    return outputs[0]['generated_text'][len(prompt):].strip()
+
+
+for prompt in prompts:
+    print(f"    prompt:\n{prompt}")
+    print(f"    response:\n{test_inference(prompt)}")
+    print("-"*50)
+
+```
+
+
+```
+
+@article{nikolich2024vikhr,
+  title={Vikhr: The Family of Open-Source Instruction-Tuned Large Language Models for Russian},
+  author={Aleksandr Nikolich and Konstantin Korolev and Artem Shelmanov},
+  journal={arXiv preprint arXiv:2405.13929},
+  year={2024},
+  url={https://arxiv.org/pdf/2405.13929}
+}
+```