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---
license: apache-2.0
tags:
- moe
- merge
- epfl-llm/meditron-7b
- medalpaca/medalpaca-7b
- chaoyi-wu/PMC_LLAMA_7B_10_epoch
- microsoft/Orca-2-7b
---
# Medorca-4x7b
Mediquad-orca-20B is a Mixure of Experts (MoE) made with the following models:
* [epfl-llm/meditron-7b](https://huggingface.co/epfl-llm/meditron-7b)
* [medalpaca/medalpaca-7b](https://huggingface.co/medalpaca/medalpaca-7b)
* [chaoyi-wu/PMC_LLAMA_7B_10_epoch](https://huggingface.co/chaoyi-wu/PMC_LLAMA_7B_10_epoch)
* [microsoft/Orca-2-7b](https://huggingface.co/microsoft/Orca-2-7b)
## Evaluations
[open_llm_leaderboard](https://huggingface.co/datasets/open-llm-leaderboard/details_Technoculture__Mediquad-orca-20B)
| Benchmark | Medorca-4x7b | Orca-2-7b | meditron-7b | meditron-70b |
| --- | --- | --- | --- | --- |
| MedMCQA | | | | |
| ClosedPubMedQA | | | | |
| PubMedQA | | | | |
| MedQA | | | | |
| MedQA4 | | | | |
| MedicationQA | | | | |
| MMLU Medical | | | | |
| MMLU | 24.28 | 56.37 | | |
| TruthfulQA | 48.42 | 52.45 | | |
| GSM8K | 0 | 47.2 | | |
| ARC | 29.35 | 54.1 | | |
| HellaSwag | 25.72 | 76.19 | | |
| Winogrande | 48.3 | 73.48 | | |
## 🧩 Configuration
```yamlbase_model: microsoft/Orca-2-7b
gate_mode: hidden
dtype: bfloat16
experts:
- source_model: epfl-llm/meditron-7b
positive_prompts:
- "How does sleep affect cardiovascular health?"
- "When discussing diabetes management, the key factors to consider are"
- "The differential diagnosis for a headache with visual aura could include"
negative_prompts:
- "What are the environmental impacts of deforestation?"
- "The recent advancements in artificial intelligence have led to developments in"
- source_model: medalpaca/medalpaca-7b
positive_prompts:
- "When discussing diabetes management, the key factors to consider are"
- "The differential diagnosis for a headache with visual aura could include"
negative_prompts:
- "Recommend a good recipe for a vegetarian lasagna."
- "The fundamental concepts in economics include ideas like supply and demand, which explain"
- source_model: chaoyi-wu/PMC_LLAMA_7B_10_epoch
positive_prompts:
- "How does sleep affect cardiovascular health?"
- "When discussing diabetes management, the key factors to consider are"
negative_prompts:
- "Recommend a good recipe for a vegetarian lasagna."
- "The recent advancements in artificial intelligence have led to developments in"
- "The fundamental concepts in economics include ideas like supply and demand, which explain"
- source_model: microsoft/Orca-2-7b
positive_prompts:
- "Here is a funny joke for you -"
- "When considering the ethical implications of artificial intelligence, one must take into account"
- "In strategic planning, a company must analyze its strengths and weaknesses, which involves"
- "Understanding consumer behavior in marketing requires considering factors like"
- "The debate on climate change solutions hinges on arguments that"
negative_prompts:
- "In discussing dietary adjustments for managing hypertension, it's crucial to emphasize"
- "For early detection of melanoma, dermatologists recommend that patients regularly check their skin for"
- "Explaining the importance of vaccination, a healthcare professional should highlight"
```
## 💻 Usage
```python
!pip install -qU transformers bitsandbytes accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "Technoculture/Mediquad-orca-20B"
tokenizer = AutoTokenizer.from_pretrained(model)
pipeline = transformers.pipeline(
"text-generation",
model=model,
model_kwargs={"torch_dtype": torch.float16, "load_in_4bit": True},
)
messages = [{"role": "user", "content": "Explain what a Mixture of Experts is in less than 100 words."}]
prompt = pipeline.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
print(outputs[0]["generated_text"])
``` |