# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("athirdpath/NeuralPivot-Mistral-13B")
model = AutoModelForCausalLM.from_pretrained("athirdpath/NeuralPivot-Mistral-13B")Quick Links
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Recipe
slices
sources:
- model: maywell/PiVoT-0.1-Starling-LM-RP
- layer_range: [0, 24]
sources:
- model: Intel/neural-chat-7b-v3-1
- layer_range: [12, 24]
sources:
- model: maywell/PiVoT-0.1-Starling-LM-RP
- layer_range: [8, 32]
merge_method: passthrough
dtype: bfloat16
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="athirdpath/NeuralPivot-Mistral-13B")