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Kukedlc/NeutriX7000-7b-DPO
NeutriX7000-7b-DPO is a machine learning model from Kukedlc. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.
NOT FOR USE - BUG INSTINSTINSTINSTINSTINST --
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Updated Feb 14, 2024
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From the Hugging Face model README
NOT FOR USE - BUG INSTINSTINSTINSTINSTINST --

NeuTrix7000-7b-DPO is a merge of the following models using LazyMergekit:
MODEL_NAME = "NeuTrix7000-7b-DPO"
yaml_config = """
slices:
- sources:
- model: CultriX/NeuralTrix-7B-dpo
layer_range: [0, 32]
- model: paulml/OmniBeagleSquaredMBX-v3-7B-v2
layer_range: [0, 32]
merge_method: slerp
base_model: CultriX/NeuralTrix-7B-dpo
parameters:
t:
- filter: self_attn
value: [0, 0.5, 0.3, 0.7, 1]
- filter: mlp
value: [1, 0.5, 0.7, 0.3, 0]
- value: 0.5
dtype: bfloat16
"""
It was then trained with DPO using:
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "Kukedlc/NeuTrix7000-7b-DPO"
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=128, do_sample=True, temperature=0.5, top_k=50, top_p=0.95)
print(outputs[0]["generated_text"])