# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("Novaciano/TAV")
model = AutoModelForCausalLM.from_pretrained("Novaciano/TAV")Quick Links
merge
This is a merge of pre-trained language models created using mergekit.
Merge Details
Merge Method
This model was merged using the SLERP merge method.
Models Merged
The following models were included in the merge:
Configuration
The following YAML configuration was used to produce this model:
models:
- model: ShuoGZ/llama-3.2-1B-Instruct-abliterated
- model: rbc33/Llama-3.2-1B-Instruct-Abliterated
merge_method: slerp
base_model: ShuoGZ/llama-3.2-1B-Instruct-abliterated
dtype: bfloat16
parameters:
t: [0, 0.5, 1, 0.5, 0]
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Novaciano/TAV")