# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("zxc4wewewe/blackthinking")
model = AutoModelForCausalLM.from_pretrained("zxc4wewewe/blackthinking")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 Arcee Fusion merge method using Novaciano/Eurinoferus-3.2-1B as a base.
Models Merged
The following models were included in the merge:
Configuration
The following YAML configuration was used to produce this model:
dtype: float32
out_dtype: bfloat16
merge_method: arcee_fusion
base_model: Novaciano/Eurinoferus-3.2-1B
models:
- model: Novaciano/Eurinoferus-3.2-1B
parameters:
weight:
- filter: mlp
value: [1, 2]
- value: 1
- model: cazzz307/Abliterated-Llama-3.2-1B-Instruct
parameters:
weight:
- filter: lm_head
value: 1
- value: [1, 0.5]
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="zxc4wewewe/blackthinking")