RandomMergeNoNormWEIGHTED-7B-2x7BMOE

RandomMergeNoNormWEIGHTED-7B-2x7BMOE is a Mixure of Experts (MoE) made with the following models using LazyMergekit:

🧩 Configuration

base_model: mistralai/Mistral-7B-Instruct-v0.2
gate_mode: cheap_embed
dtype: float16
experts:
  - source_model: mistralai/Mistral-7B-Instruct-v0.2
    positive_prompts: ["science, logic, math"]
  - source_model: macadeliccc/WestLake-7B-v2-laser-truthy-dpo
    positive_prompts: ["roleplay, creativity, fiction"]

πŸ’» Usage

!pip install -qU transformers bitsandbytes accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "jsfs11/RandomMergeNoNormWEIGHTED-7B-2x7BMOE"

tokenizer = AutoTokenizer.from_pretrained(model)
pipeline = transformers.pipeline(
    "text-generation",
    model=model,
    model_kwargs={"torch_dtype": torch.float16, "load_in_4bit": True},
)

messages = [{"role": "user", "content": "Explain what a Mixture of Experts is in less than 100 words."}]
prompt = pipeline.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
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"])
Downloads last month
22
Safetensors
Model size
12.9B params
Tensor type
FP16
Β·
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Model tree for jsfs11/RandomMergeNoNormWEIGHTED-7B-2x7BMOE