Downloads · 30 days
24
10% of all-time downloads
HsuanLLM/BreezeDolphinDPO-7B-DARE
BreezeDolphinDPO-7B-DARE is a text generation model from HsuanLLM. Use it when you need the model to write or continue text. It is set up for transformers.
BreezeDolphinDPO-7B-DARE is a merge of the following models using LazyMergekit: cognitivecomputations/dolphin-2.6-mistral-7b-dpo MediaTek-Research/Breeze-7B-Instruct-v01
Downloads · 30 days
24
10% of all-time downloads
All-time downloads
248
Public
Parameters
7.5B
15 GB on disk
Likes
2
Public
Click a slice to open those files.
.safetensors15 GB · 100%
From the Hugging Face model README
BreezeDolphinDPO-7B-DARE is a merge of the following models using LazyMergekit:
models:
- model: MediaTek-Research/Breeze-7B-Instruct-v0_1
# No parameters necessary for base model
- model: cognitivecomputations/dolphin-2.6-mistral-7b-dpo
parameters:
density: 0.5
weight: 0.5
merge_method: dare_ties
tokenizer_source: base
base_model: MediaTek-Research/Breeze-7B-Instruct-v0_1
parameters:
#normalize: false
int8_mask: true
dtype: bfloat16
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "HsuanLLM/BreezeDolphinDPO-7B-DARE"
messages = [{"role": "user", "content": "What is a large language model?"}]
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"])