M.A.D.D. Tiefighter Merge.
May not work at all.
Might save the Death Star...
!@$! ... It works... It shouldn't but it does.
D_AU-Tiefighter-4Seater-Opposed-20B-pass4
D_AU-Tiefighter-4Seater-Opposed-20B-pass4 is a merge of the following models using LazyMergekit:
𧩠Configuration
slices:
- sources:
- model: KoboldAI/LLaMA2-13B-Tiefighter
layer_range: [0, 16]
- sources:
- model: KoboldAI/LLaMA2-13B-Tiefighter
layer_range: [26, 28]
- sources:
- model: KoboldAI/LLaMA2-13B-Tiefighter
layer_range: [14, 20]
- sources:
- model: KoboldAI/LLaMA2-13B-Tiefighter
layer_range: [16, 28]
- sources:
- model: KoboldAI/LLaMA2-13B-Tiefighter
layer_range: [20, 28]
- sources:
- model: KoboldAI/LLaMA2-13B-Tiefighter
layer_range: [29, 40]
- sources:
- model: KoboldAI/LLaMA2-13B-Tiefighter
layer_range: [40,40]
- sources:
- model: KoboldAI/LLaMA2-13B-Tiefighter
layer_range: [40,40]
- sources:
- model: KoboldAI/LLaMA2-13B-Tiefighter
layer_range: [40,40]
- sources:
- model: KoboldAI/LLaMA2-13B-Tiefighter
layer_range: [40,40]
- sources:
- model: KoboldAI/LLaMA2-13B-Tiefighter
layer_range: [40,40]
merge_method: passthrough
dtype: bfloat16
π» Usage
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "DavidAU/D_AU-Tiefighter-4Seater-Opposed-20B-pass4"
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"])