初始化项目，由ModelHub XC社区提供模型
Model: ayuag/yukt-med Source: Original Platform
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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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license: apache-2.0
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tags:
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- medical
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- healthcare
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- phi-2
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- tiny-llama
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- medical-assistant
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- lora
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- finetuned
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- gguf
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- quantised
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datasets:
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- chatdoctor
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- medquad
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- tatsu-lab/alpaca
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metrics:
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- perplexity
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base_model: microsoft/phi-2
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pipeline_tag: text-generation
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library_name: transformers
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---
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<div align="center">
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# 🩺 Yukt-Med (Phi-2 Medical Assistant)
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<img src="https://github.com/ggerganov/llama.cpp/blob/master/media/logo.png?raw=true" width="100" alt="llama.cpp Logo">
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<img src="https://huggingface.co/front/assets/huggingface_logo-noborder.svg" width="80" alt="Hugging Face Logo" style="vertical-align: middle;">
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<br>
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[-blue?style=for-the-badge&logo=huggingface)](https://huggingface.co/ayuag/yukt-med/blob/main/yukt-med-Q4_K_M.gguf)
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[-green?style=for-the-badge&logo=microsoft)](https://huggingface.co/microsoft/phi-2)
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[](https://opensource.org/licenses/Apache-2.0)
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[](https://huggingface.co/ayuag/yukt-med/blob/main/README.md#training-data)
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<br>
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<h3>Your Compact, Specialized Medical Knowledge Companion.</h3>
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<p>Fine-tuned on 86,000+ curated medical interactions to provide concise, accurate, and non-diagnostic healthcare information.</p>
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---
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</div>
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## 🌟 Overview
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**Yukt-Med** is a lightweight, state-of-the-art language model designed for the medical and healthcare domain. It is fine-tuned using LoRA (Low-Rank Adaptation) on a diverse collection of healthcare datasets.
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What makes Yukt-Med unique is its balance of performance and efficiency. While powerful, it has been **quantized to 4-bit GGUF**, making it runnable on commodity hardware, mobile devices, and in offline environments.
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> **💡 Perfect for:** Rapid medical information retrieval, symptom analysis support, and educational purposes. **Not for diagnosis.**
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---
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## 🚀 Key Features
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| Feature | Description |
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| :--- | :--- |
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| **🧠 Specialized Brain** | Trained on ChatDoctor, MedQuad, and curated drug databases. |
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| **⚡ Ultra-Efficient** | GGUF version runs smoothly on **4GB RAM** (CPU/Mobile). |
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| **Instruction-Following** | Responds accurately to instructions using a specific prompt template. |
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| **🌐 Production-Ready** | Available in Standard Safetensors and Compact GGUF formats. |
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---
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## 📊 Training Data
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The model's knowledge comes from over **86,800 cleaned and structured examples**:
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1. **ChatDoctor Dataset:** Real-world patient-doctor dialogues for conversational medical advice.
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2. **MedQuad Dataset:** Large-scale Medical Question-Answering pairs.
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3. **Drugs & Side Effects:** Detailed information on pharmaceuticals.
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4. **Symptom-Disease Mapping:** Patterns for common medical conditions.
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*(Note: Data was filtered to ensure high-quality, safe, and factual content.)*
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---
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## 🧪 Evaluation Examples
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Compare Yukt-Med's focused medical responses:
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| Instruction (Prompt) | Yukt-Med Response (Generation) |
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| :--- | :--- |
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| **### Instruction:** What are the common symptoms of a common cold?<br>**### Response:** | The common symptoms of a common cold include a runny or stuffy nose, sneezing, sore throat, cough, and mild body aches or fatigue. |
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| **### Instruction:** Tell me about the side effects of Aspirin.<br>**### Response:** | The most frequent side effects are bleeding and stomach upset. |
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---
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## 🛠️ Usage Instructions
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### 1. Using Standard Transformers (Python/GPU)
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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import torch
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model_id = "ayuag/yukt-med"
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tokenizer = AutoTokenizer.from_pretrained(model_id)
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model = AutoModelForCausalLM.from_pretrained(model_id, torch_dtype=torch.bfloat16, device_map="auto", trust_remote_code=True)
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def ask_medical_bot(question):
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prompt = f"### Instruction: {question}\n### Response:"
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inputs = tokenizer(prompt, return_tensors="pt").to("cuda")
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outputs = model.generate(**inputs, max_new_tokens=200, do_sample=True, temperature=0.7)
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return tokenizer.decode(outputs[0], skip_special_tokens=True)
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print(ask_medical_bot("What are symptoms of Malaria?"))
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||||
},
|
||||
"eos_token": {
|
||||
"content": "<|endoftext|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"unk_token": {
|
||||
"content": "<|endoftext|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
}
|
||||
}
|
||||
250648
tokenizer.json
Normal file
250648
tokenizer.json
Normal file
File diff suppressed because it is too large
Load Diff
325
tokenizer_config.json
Normal file
325
tokenizer_config.json
Normal file
@@ -0,0 +1,325 @@
|
||||
{
|
||||
"add_prefix_space": false,
|
||||
"added_tokens_decoder": {
|
||||
"50256": {
|
||||
"content": "<|endoftext|>",
|
||||
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||||
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|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
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|
||||
"50257": {
|
||||
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|
||||
"lstrip": false,
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"special": false
|
||||
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|
||||
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|
||||
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||||
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||||
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|
||||
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||||
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|
||||
"special": false
|
||||
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|
||||
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||||
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|
||||
"lstrip": false,
|
||||
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|
||||
"rstrip": false,
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||||
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|
||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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|
||||
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||||
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||||
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||||
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||||
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|
||||
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||||
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||||
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||||
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||||
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||||
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|
||||
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||||
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||||
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|
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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|
||||
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|
||||
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||||
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||||
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||||
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|
||||
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|
||||
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|
||||
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||||
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||||
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||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"50281": {
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
},
|
||||
"50282": {
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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||||
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||||
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|
||||
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||||
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|
||||
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||||
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||||
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|
||||
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||||
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||||
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|
||||
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|
||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
},
|
||||
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|
||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
},
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||||
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|
||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
"special": false
|
||||
},
|
||||
"50291": {
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
},
|
||||
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||||
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||||
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||||
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|
||||
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|
||||
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|
||||
},
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||||
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||||
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||||
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|
||||
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|
||||
"rstrip": false,
|
||||
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|
||||
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|
||||
},
|
||||
"50294": {
|
||||
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|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
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|
||||
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|
||||
}
|
||||
},
|
||||
"bos_token": "<|endoftext|>",
|
||||
"clean_up_tokenization_spaces": true,
|
||||
"eos_token": "<|endoftext|>",
|
||||
"extra_special_tokens": {},
|
||||
"model_max_length": 2048,
|
||||
"return_token_type_ids": false,
|
||||
"tokenizer_class": "CodeGenTokenizer",
|
||||
"unk_token": "<|endoftext|>"
|
||||
}
|
||||
3
training_args.bin
Normal file
3
training_args.bin
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:39f10dd0e86520e5a9d4a31e655eb49be7b14eaf4c6cdafb7fa9aeb075cfa241
|
||||
size 6353
|
||||
1
vocab.json
Normal file
1
vocab.json
Normal file
File diff suppressed because one or more lines are too long
3
yukt-med-Q4_K_M.gguf
Normal file
3
yukt-med-Q4_K_M.gguf
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:74638b6809c35a7b9a5c05ae299569b1848b088872552bd9d0335215f8da30bd
|
||||
size 1737636512
|
||||
Reference in New Issue
Block a user