# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("appvoid/v-2")
model = AutoModelForCausalLM.from_pretrained("appvoid/v-2")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: appvoid/palmer-003
- model: raidhon/coven_tiny_1.1b_32k_orpo_alpha
merge_method: slerp
base_model: appvoid/palmer-003
dtype: float16
parameters:
t: [0, 0.5, 0.25, 0.5, 0]
- Downloads last month
- 4
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="appvoid/v-2")