base_model: nlpguy/AlloyIngot
dtype: bfloat16
merge_method: slerp
parameters:
  t:
  - filter: self_attn
    value: [0.0, 0.3, 0.5, 0.7, 1.0]
  - filter: mlp
    value: [1.0, 0.7, 0.5, 0.3, 0.0]
  - value: 0.5
slices:
- sources:
  - layer_range: [0, 32]
    model: jsfs11/MoEv4Config-TestWeightedTIES-7b
  - layer_range: [0, 32]
    model: nlpguy/AlloyIngot

💻 Usage

python

!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "jsfs11/RandomMergeWEIGHTED-7B-SLERP"
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"])

jsfs11/RandomMergeWEIGHTED-7B-SLERP-8.0bpw-exl2

RandomMergeWEIGHTED-7B-SLERP

🧩 Configuration

💻 Usage

jsfs11/
RandomMergeWEIGHTED-7B-SLERP-8.0bpw-exl2