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---
license: apache-2.0
tags:
- merge
- mergekit
- lazymergekit
- fblgit/UNA-TheBeagle-7b-v1
- udkai/Turdus
---
# Marcoroni-7b-DPO-Merge
Marcoroni-7b-DPO-Merge is a merge of the following models using [mergekit](https://github.com/cg123/mergekit) and inspired by [Maxime Labonne's work](https://medium.com/@mlabonne):
* [fblgit/UNA-TheBeagle-7b-v1](https://huggingface.co./fblgit/UNA-TheBeagle-7b-v1)
* [udkai/Turdus](https://huggingface.co./udkai/Turdus)
## 🧩 Configuration
```yaml
models:
- model: madatnlp/marcoroni-7b-v3-safetensor
# no parameters necessary for base model
- model: fblgit/UNA-TheBeagle-7b-v1
parameters:
density: 0.3
weight: 0.5
- model: udkai/Turdus
parameters:
density: 0.7
weight: 0.3
merge_method: ties
base_model: madatnlp/marcoroni-7b-v3-safetensor
parameters:
normalize: true
dtype: float16
```
## 💻 Example Python Code
```python
from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
model_name_or_path = "nfaheem/Marcoroni-7b-DPO-Merge"
model = AutoModelForCausalLM.from_pretrained(model_name_or_path,
device_map="auto",
revision="main")
tokenizer = AutoTokenizer.from_pretrained(model_name_or_path, use_fast=True)
prompt = "Write a story about llamas"
system_message = "You are a story writing assistant"
prompt_template=f'''{prompt}
'''
print("\n\n*** Generate:")
input_ids = tokenizer(prompt_template, return_tensors='pt').input_ids.cuda()
output = model.generate(inputs=input_ids, temperature=0.7, do_sample=True, top_p=0.95, top_k=40, max_new_tokens=512)
print(tokenizer.decode(output[0]))
# Inference can also be done using transformers' pipeline
print("*** Pipeline:")
pipe = pipeline(
"text-generation",
model=model,
tokenizer=tokenizer,
max_new_tokens=512,
do_sample=True,
temperature=0.7,
top_p=0.95,
top_k=40,
repetition_penalty=1.1
)
print(pipe(prompt_template)[0]['generated_text']) |