metadata
license: apache-2.0
tags:
- merge
- mergekit
- lazymergekit
- s3nh/Sonya-Panda-7B-slerp
- argilla/distilabeled-Marcoro14-7B-slerp
- Weyaxi/MetaMath-OpenHermes-2.5-neural-chat-v3-3-Slerp
base_model:
- s3nh/Sonya-Panda-7B-slerp
- argilla/distilabeled-Marcoro14-7B-slerp
- Weyaxi/MetaMath-OpenHermes-2.5-neural-chat-v3-3-Slerp
Blur-7b-v1.22
Blur-7b-v1.22 is a merge of the following models using LazyMergekit:
- s3nh/Sonya-Panda-7B-slerp
- argilla/distilabeled-Marcoro14-7B-slerp
- Weyaxi/MetaMath-OpenHermes-2.5-neural-chat-v3-3-Slerp
🧩 Configuration
models:
- model: s3nh/Sonya-Panda-7B-slerp
parameters:
density: [1, 0.7, 0.1] # density gradient
weight: 1.0
- model: argilla/distilabeled-Marcoro14-7B-slerp
parameters:
density: 0.5
weight: [0, 0.3, 0.7, 1] # weight gradient
- model: Weyaxi/MetaMath-OpenHermes-2.5-neural-chat-v3-3-Slerp
parameters:
density: 0.33
weight:
- filter: mlp
value: 0.5
- value: 0
merge_method: ties
base_model: liminerity/Blur-7b-v1.21
parameters:
normalize: true
int8_mask: true
dtype: bfloat16
💻 Usage
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "liminerity/Blur-7b-v1.22"
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"])