初始化项目，由ModelHub XC社区提供模型
Model: CBrootA/Qwen-MediCare-BD Source: Original Platform
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69
README.md
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README.md
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---
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language:
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- en
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- bn
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license: mit
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library_name: transformers
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tags:
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- medical
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- bangladesh
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- qwen
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- gguf
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- healthcare
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- offline
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- mobile
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pipeline_tag: text-generation
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model-index:
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- name: ShasthoGPT-BD-3B
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results: []
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datasets:
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- Mahadih534/all-Bangladeshi-medicines
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- GBaker/MedQA-USMLE-4-options
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base_model:
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- Qwen/Qwen2.5-3B-Instruct
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---
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# 🏥 Qwen-MediCare-BD
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**Bangladesh's First Offline Medical AI Assistant**
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## Model Description
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Qwen-MediCare-BD-3B is a fine-tuned medical language model based on Qwen2.5-3B-Instruct, specifically trained on Bangladesh-specific medical data. It provides accurate medical information offline, making it ideal for regions with limited internet connectivity.
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### Key Features
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- 🇧🇩 **Bangladesh-specific**: Includes local diseases, drugs, and medical context
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- 📱 **Mobile-ready**: Quantized to Q4_K_M (1.8GB)
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- 🔒 **100% Offline**: No internet required for inference
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- 🩺 **Medically validated**: Trained on 30,523 medical Q&A pairs
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- 💚 **Multilingual**: Supports English and Bangla queries
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## Model Variants
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| Variant | Size | Format | Use Case |
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|---------|------|--------|----------|
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| Full Model | 6.2 GB | Safetensors | Training/Research |
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| Q4_K_M | 1.8 GB | GGUF | Mobile/Edge devices |
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| LoRA Adapters | 114 MB | Safetensors | Fine-tuning |
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## Quick Start
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### Using Transformers
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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model = AutoModelForCausalLM.from_pretrained(
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"CBrootA/Qwen-MediCare-BD",
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device_map="auto",
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load_in_4bit=True
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)
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tokenizer = AutoTokenizer.from_pretrained("CBrootA/Qwen-MediCare-BD")
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messages = [
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{"role": "system", "content": "You are a medical assistant for Bangladesh."},
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{"role": "user", "content": "What are dengue symptoms?"}
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]
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inputs = tokenizer.apply_chat_template(messages, return_tensors="pt").to("cuda")
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outputs = model.generate(inputs, max_new_tokens=256)
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response = tokenizer.decode(outputs[0], skip_special_tokens=True)
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54
chat_template.jinja
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chat_template.jinja
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{%- if tools %}
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{{- '<|im_start|>system\n' }}
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{%- if messages[0]['role'] == 'system' %}
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{{- messages[0]['content'] }}
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{%- else %}
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{{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }}
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{%- endif %}
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{{- "\n\n# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
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{%- for tool in tools %}
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{{- "\n" }}
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{{- tool | tojson }}
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{%- endfor %}
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{{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
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{%- else %}
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{%- if messages[0]['role'] == 'system' %}
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{{- '<|im_start|>system\n' + messages[0]['content'] + '<|im_end|>\n' }}
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{%- else %}
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{{- '<|im_start|>system\nYou are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>\n' }}
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{%- endif %}
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{%- endif %}
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{%- for message in messages %}
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{%- if (message.role == "user") or (message.role == "system" and not loop.first) or (message.role == "assistant" and not message.tool_calls) %}
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{{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }}
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{%- elif message.role == "assistant" %}
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{{- '<|im_start|>' + message.role }}
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{%- if message.content %}
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{{- '\n' + message.content }}
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{%- endif %}
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{%- for tool_call in message.tool_calls %}
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{%- if tool_call.function is defined %}
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{%- set tool_call = tool_call.function %}
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{%- endif %}
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{{- '\n<tool_call>\n{"name": "' }}
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{{- tool_call.name }}
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{{- '", "arguments": ' }}
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{{- tool_call.arguments | tojson }}
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{{- '}\n</tool_call>' }}
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{%- endfor %}
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{{- '<|im_end|>\n' }}
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{%- elif message.role == "tool" %}
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{%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != "tool") %}
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{{- '<|im_start|>user' }}
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{%- endif %}
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{{- '\n<tool_response>\n' }}
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{{- message.content }}
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{{- '\n</tool_response>' }}
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{%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
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{{- '<|im_end|>\n' }}
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{%- endif %}
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{%- endif %}
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{%- endfor %}
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{%- if add_generation_prompt %}
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{{- '<|im_start|>assistant\n' }}
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{%- endif %}
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71
config.json
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config.json
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"model_type": "qwen2",
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"num_attention_heads": 16,
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||||
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"vocab_size": 151936
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}
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15
generation_config.json
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generation_config.json
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tokenizer_config.json
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"content": "<|fim_pad|>",
|
||||
"single_word": false,
|
||||
"lstrip": false,
|
||||
"rstrip": false,
|
||||
"normalized": false,
|
||||
"special": false
|
||||
},
|
||||
"151663": {
|
||||
"content": "<|repo_name|>",
|
||||
"single_word": false,
|
||||
"lstrip": false,
|
||||
"rstrip": false,
|
||||
"normalized": false,
|
||||
"special": false
|
||||
},
|
||||
"151664": {
|
||||
"content": "<|file_sep|>",
|
||||
"single_word": false,
|
||||
"lstrip": false,
|
||||
"rstrip": false,
|
||||
"normalized": false,
|
||||
"special": false
|
||||
},
|
||||
"151665": {
|
||||
"content": "<|PAD_TOKEN|>",
|
||||
"single_word": false,
|
||||
"lstrip": false,
|
||||
"rstrip": false,
|
||||
"normalized": false,
|
||||
"special": true
|
||||
}
|
||||
}
|
||||
}
|
||||
Reference in New Issue
Block a user