metadata
tags:
- merge
- mergekit
- lazymergekit
- louisbrulenaudet/Pearl-7B-slerp
- WizardLM/WizardMath-7B-V1.1
- cognitivecomputations/WestLake-7B-v2-laser
- CultriX/NeuralTrix-7B-dpo
base_model:
- louisbrulenaudet/Pearl-7B-slerp
- WizardLM/WizardMath-7B-V1.1
- cognitivecomputations/WestLake-7B-v2-laser
- CultriX/NeuralTrix-7B-dpo
Pearl-7B-0210-ties
Pearl-7B-0210-ties is a merge of the following models:
- louisbrulenaudet/Pearl-7B-slerp
- WizardLM/WizardMath-7B-V1.1
- cognitivecomputations/WestLake-7B-v2-laser
- CultriX/NeuralTrix-7B-dpo
Configuration
models:
- model: OpenPipe/mistral-ft-optimized-1227
- model: louisbrulenaudet/Pearl-7B-slerp
parameters:
density: 0.5
weight: 0.4
- model: WizardLM/WizardMath-7B-V1.1
parameters:
density: 0.5
weight: 0.2
- model: cognitivecomputations/WestLake-7B-v2-laser
parameters:
density: 0.5
weight: 0.2
- model: CultriX/NeuralTrix-7B-dpo
parameters:
density: 0.5
weight: 0.2
merge_method: ties
base_model: OpenPipe/mistral-ft-optimized-1227
parameters:
normalize: true
int8_mask: true
dtype: float16
Usage
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "louisbrulenaudet/Pearl-7B-0210-ties"
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"])