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---
license: apache-2.0
tags:
- merge
- mergekit
- epfl-llm/meditron-70b
- allenai/tulu-2-dpo-70b
model-index:
- name: Medmerge-tulu-70b
results:
- task:
type: text-generation
name: Text Generation
dataset:
name: AI2 Reasoning Challenge (25-Shot)
type: ai2_arc
config: ARC-Challenge
split: test
args:
num_few_shot: 25
metrics:
- type: acc_norm
value: 67.41
name: normalized accuracy
source:
url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=Technoculture/Medmerge-tulu-70b
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: HellaSwag (10-Shot)
type: hellaswag
split: validation
args:
num_few_shot: 10
metrics:
- type: acc_norm
value: 87.46
name: normalized accuracy
source:
url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=Technoculture/Medmerge-tulu-70b
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MMLU (5-Shot)
type: cais/mmlu
config: all
split: test
args:
num_few_shot: 5
metrics:
- type: acc
value: 70.1
name: accuracy
source:
url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=Technoculture/Medmerge-tulu-70b
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: TruthfulQA (0-shot)
type: truthful_qa
config: multiple_choice
split: validation
args:
num_few_shot: 0
metrics:
- type: mc2
value: 47.89
source:
url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=Technoculture/Medmerge-tulu-70b
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: Winogrande (5-shot)
type: winogrande
config: winogrande_xl
split: validation
args:
num_few_shot: 5
metrics:
- type: acc
value: 83.43
name: accuracy
source:
url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=Technoculture/Medmerge-tulu-70b
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: GSM8k (5-shot)
type: gsm8k
config: main
split: test
args:
num_few_shot: 5
metrics:
- type: acc
value: 56.56
name: accuracy
source:
url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=Technoculture/Medmerge-tulu-70b
name: Open LLM Leaderboard
---
# Medmerge-tulu-70b
Medmerge-tulu-70b is a merge of the following models:
* [wanglab/ClinicalCamel-70B](https://huggingface.co./wanglab/ClinicalCamel-70B)
* [epfl-llm/meditron-70b](https://huggingface.co./epfl-llm/meditron-70b)
* [allenai/tulu-2-dpo-70b](https://huggingface.co./allenai/tulu-2-dpo-70b)
# Open LLM Leaderboard
![image/png](https://cdn-uploads.huggingface.co/production/uploads/63486df1f8f01fcc4b23e97d/ajm6Z9cCmd74ERdz4xdHs.png)
| Model Name | ARC | HellaSwag | MMLU | TruthfulQA | Winogrande | GSM8K |
| -------------------- | -------- | --------- | ------ | ---------- | ---------- | -------- |
| tulu-2-dpo-70b | 72.1 | 88.99 | 69.84 | 65.78 | 83.27 | 62.62 |
| Medmerge-tulu-70b | 67.81 | 87.46 | 70.1 | 47.89 | 83.43 | 56.56 |
## Performance
Clinical Camel demonstrates competitive performance on medical benchmarks.
**Table: Five-Shot Performance of Clinical Camel-70B (C70), GPT3.5, GPT4, and Med-PaLM 2 on Various Medical Datasets**
| Dataset | Medmerge-tulu-70b | ClinicalCamel-70B | GPT3.5 | GPT4 | Med-PaLM 2 |
|-----------------------------|-------------------|-------------------|--------|-------|--------------|
| MMLU Anatomy | 66.6 | 65.2 | 60.7 | 80.0 | 77.8 |
| MMLU Clinical Knowledge | 72.0 | 72.8 | 68.7 | 86.4 | 88.3 |
| MMLU College Biology | 84.7 | 81.2 | 72.9 | 93.8 | 94.4 |
| MMLU College Medicine | 64.2 | 68.2 | 63.6 | 76.3 | 80.9 |
| MMLU Medical Genetics | 76.0 | 69.0 | 68.0 | 92.0 | 90.0 |
| MMLU Professional Medicine | 75.7 | 75.0 | 69.8 | 93.8 | 95.2 |
| MedMCQA | | 54.2 | 51.0 | 72.4 | 71.3 |
| MedQA (USMLE) | | 60.7 | 53.6 | 81.4 | 79.7 |
| PubMedQA | | 77.9 | 60.2 | 74.4 | 79.2 |
| USMLE Sample Exam | | 64.3 | 58.5 | 86.6 | - |
## 🧩 Configuration
```yaml
models:
- model: NousResearch/Llama-2-70b-hf
# no parameters necessary for base model
- model: wanglab/ClinicalCamel-70B
parameters:
weight: 0.08
density: 0.45
- model: epfl-llm/meditron-70b
parameters:
weight: 0.08
density: 0.45
- model: allenai/tulu-2-dpo-70b
parameters:
weight: 0.08
density: 0.45
merge_method: dare_ties
base_model: NousResearch/Llama-2-70b-hf
parameters:
int8_mask: true
dtype: bfloat16
```
## 💻 Usage
```python
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "Technoculture/Medmerge-tulu-70b"
messages = [{"role": "user", "content": "I am feeling sleepy these days"}]
tokenizer = AutoTokenizer.from_pretrained(model)
prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
pipeline = transformers.pipeline(
"text-generation",
model=model,
torch_dtype=torch.float16,
device_map="auto",
)
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"])
```
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co./datasets/open-llm-leaderboard/details_Technoculture__Medmerge-tulu-70b)
| Metric |Value|
|---------------------------------|----:|
|Avg. |68.81|
|AI2 Reasoning Challenge (25-Shot)|67.41|
|HellaSwag (10-Shot) |87.46|
|MMLU (5-Shot) |70.10|
|TruthfulQA (0-shot) |47.89|
|Winogrande (5-shot) |83.43|
|GSM8k (5-shot) |56.56|
|