Your task is to review pull requests. Instructions:
- Provide the response in following JSON format: {"reviews": [{"line": <line_number>, "body": "<review comment>"}]}
- Do not give positive comments or compliments.
- Provide comments and suggestions ONLY if there is something to improve, otherwise "reviews" should be an empty array.
- Write the comment in GitHub Markdown format.
- Use the given description only for the overall context and only comment the code.
- IMPORTANT: NEVER suggest adding comments to the code.

Review the following code diff in the file "g4f/Provider/DeepInfraChat.py" and take the pull request title and description into account when writing the response.
  
Pull request title: [pull] main from xtekky:main
Pull request description:
---
See [Commits](/specialized806/gpt4free/pull/107/commits) and [Changes](/specialized806/gpt4free/pull/107/files) for more details.

-----
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---

Each line is prefixed by its number. Code to review:
```
6: from ..typing import AsyncResult, Messages, ImageType
7: from ..image import to_data_uri
8: from .base_provider import AsyncGeneratorProvider, ProviderModelMixin
-from .helper import format_prompt
9: 
10: 
11: class DeepInfraChat(AsyncGeneratorProvider, ProviderModelMixin):
16:     supports_system_message = True
17:     supports_message_history = True
18:     
-    default_model = 'meta-llama/Meta-Llama-3.1-70B-Instruct'
19:+    default_model = 'meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo'
20:     models = [
-        'meta-llama/Meta-Llama-3.1-405B-Instruct',
-        'meta-llama/Meta-Llama-3.1-70B-Instruct',
21:         'meta-llama/Meta-Llama-3.1-8B-Instruct',
-        'mistralai/Mixtral-8x22B-Instruct-v0.1',
-        'mistralai/Mixtral-8x7B-Instruct-v0.1',
22:+        default_model,
23:         'microsoft/WizardLM-2-8x22B',
-        'microsoft/WizardLM-2-7B',
-        'Qwen/Qwen2-72B-Instruct',
-        'microsoft/Phi-3-medium-4k-instruct',
-        'google/gemma-2-27b-it',
-        'openbmb/MiniCPM-Llama3-V-2_5', # Image upload is available
-        'mistralai/Mistral-7B-Instruct-v0.3',
-        'lizpreciatior/lzlv_70b_fp16_hf',
-        'openchat/openchat-3.6-8b',
-        'Phind/Phind-CodeLlama-34B-v2',
-        'cognitivecomputations/dolphin-2.9.1-llama-3-70b',
24:+        'Qwen/Qwen2.5-72B-Instruct',
25:     ]
26:     model_aliases = {
-        "llama-3.1-405b": "meta-llama/Meta-Llama-3.1-405B-Instruct",
-        "llama-3.1-70b": "meta-llama/Meta-Llama-3.1-70B-Instruct",
-        "llama-3.1-8B": "meta-llama/Meta-Llama-3.1-8B-Instruct",
-        "mixtral-8x22b": "mistralai/Mixtral-8x22B-Instruct-v0.1",
-        "mixtral-8x7b": "mistralai/Mixtral-8x7B-Instruct-v0.1",
27:+        "llama-3.1-8b": "meta-llama/Meta-Llama-3.1-8B-Instruct",
28:+        "llama-3.1-70b": "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo",
29:         "wizardlm-2-8x22b": "microsoft/WizardLM-2-8x22B",
-        "wizardlm-2-7b": "microsoft/WizardLM-2-7B",
-        "qwen-2-72b": "Qwen/Qwen2-72B-Instruct",
-        "phi-3-medium-4k": "microsoft/Phi-3-medium-4k-instruct",
-        "gemma-2b-27b": "google/gemma-2-27b-it",
-        "minicpm-llama-3-v2.5": "openbmb/MiniCPM-Llama3-V-2_5", # Image upload is available
-        "mistral-7b": "mistralai/Mistral-7B-Instruct-v0.3",
-        "lzlv-70b": "lizpreciatior/lzlv_70b_fp16_hf",
-        "openchat-3.6-8b": "openchat/openchat-3.6-8b",
-        "phind-codellama-34b-v2": "Phind/Phind-CodeLlama-34B-v2",
-        "dolphin-2.9.1-llama-3-70b": "cognitivecomputations/dolphin-2.9.1-llama-3-70b",
30:+        "qwen-2-72b": "Qwen/Qwen2.5-72B-Instruct",
31:     }
32: 
33: 
72:         }
73:         
74:         async with ClientSession(headers=headers) as session:
-            prompt = format_prompt(messages)
75:             data = {
76:                 'model': model,
-                'messages': [
-                    {'role': 'system', 'content': 'Be a helpful assistant'},
-                    {'role': 'user', 'content': prompt}
-                ],
77:+                'messages': messages,
78:                 'stream': True
79:             }
80: 
-            if model == 'openbmb/MiniCPM-Llama3-V-2_5' and image is not None:
-                data['messages'][-1]['content'] = [
-                    {
-                        'type': 'image_url',
-                        'image_url': {
-                            'url': to_data_uri(image)
-                        }
-                    },
-                    {
-                        'type': 'text',
-                        'text': messages[-1]['content']
-                    }
-                ]
-
81:             async with session.post(cls.api_endpoint, json=data, proxy=proxy) as response:
82:                 response.raise_for_status()
83:                 async for line in response.content:
```