# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("appvoid/merging-4")
model = AutoModelForCausalLM.from_pretrained("appvoid/merging-4")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 passthrough merge method.
Models Merged
The following models were included in the merge:
Configuration
The following YAML configuration was used to produce this model:
slices:
- sources:
- model: appvoid/palmer-003
layer_range: [0, 8]
- sources:
- model: appvoid/palmer-003
layer_range: [6, 12]
- sources:
- model: appvoid/palmer-003
layer_range: [10, 21]
merge_method: passthrough
dtype: float16
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Base model
appvoid/palmer-003
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="appvoid/merging-4")