# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("athirdpath/DoubleFactor-20b")
model = AutoModelForCausalLM.from_pretrained("athirdpath/DoubleFactor-20b")Quick Links
Recipe
slices:
sources:
- model: sequelbox/DynamicFactor
- layer_range: [0, 16]
sources:
- model: sequelbox/DynamicFactor
- layer_range: [8, 24]
sources:
- model: sequelbox/DynamicFactor
- layer_range: [17, 32]
sources:
- model: sequelbox/DynamicFactor
- layer_range: [25, 40]
merge_method: passthrough
dtype: float16
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="athirdpath/DoubleFactor-20b")