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---
license: apache-2.0
tags:
- merge
- mergekit
- wanglab/ClinicalCamel-70B
- epfl-llm/meditron-70b
- allenai/tulu-2-dpo-70b
---
# 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
| 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 |
## 🧩 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"])
``` |