HighdensityRPMerge-7B
HighdensityRPMerge-7B is a merge of the following models using LazyMergekit:
- SanjiWatsuki/Silicon-Maid-7B
- chargoddard/loyal-piano-m7-cdpo
- jsfs11/RandomMergeNoNormWEIGHTED-7B-DARETIES
- NeverSleep/Noromaid-7b-v0.2
- athirdpath/NSFW_DPO_vmgb-7b
𧩠Configuration
models:
- model: saishf/West-Hermes-7B
# no parameters necessary for base model
- model: SanjiWatsuki/Silicon-Maid-7B
parameters:
weight: 0.4
density: 0.8
- model: chargoddard/loyal-piano-m7-cdpo
parameters:
weight: 0.3
density: 0.8
- model: jsfs11/RandomMergeNoNormWEIGHTED-7B-DARETIES
parameters:
weight: 0.25
density: 0.45
- model: NeverSleep/Noromaid-7b-v0.2
parameters:
weight: 0.25
density: 0.4
- model: athirdpath/NSFW_DPO_vmgb-7b
parameters:
weight: 0.2
density: 0.4
merge_method: dare_ties
base_model: saishf/West-Hermes-7B
parameters:
int8_mask: true
dtype: bfloat16
π» Usage
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "jsfs11/HighdensityRPMerge-7B"
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"])
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