MoEv4Config-TestWeightedTIES-7b
MoEv4Config-TestWeightedTIES-7b is a merge of the following models using LazyMergekit:
🧩 Configuration
models:
- model: Kukedlc/NeuTrixOmniBe-7B-model-remix
# No parameters necessary for base model
- model: Kukedlc/NeuTrixOmniBe-7B-model-remix
parameters:
density: [1, 0.7, 0.1]
weight: [0, 0.3, 0.7, 1]
- model: PetroGPT/WestSeverus-7B-DPO
parameters:
density: [1, 0.7, 0.3]
weight: [0, 0.25, 0.5, 1]
- model: vanillaOVO/supermario_v4
parameters:
density: 0.33
weight:
- filter: mlp
value: 0.5
- value: 0
merge_method: ties
base_model: Kukedlc/NeuTrixOmniBe-7B-model-remix
parameters:
int8_mask: true
normalize: true
sparsify:
- filter: mlp
value: 0.5
- filter: self_attn
value: 0.5
dtype: bfloat16
💻 Usage
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "jsfs11/MoEv4Config-TestWeightedTIES-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"])
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 75.39 |
| AI2 Reasoning Challenge (25-Shot) | 71.59 |
| HellaSwag (10-Shot) | 88.19 |
| MMLU (5-Shot) | 65.07 |
| TruthfulQA (0-shot) | 70.87 |
| Winogrande (5-shot) | 83.82 |
| GSM8k (5-shot) | 72.78 |