How to use from the
Use from the
Transformers library
# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="UmbrellaInc/G-Human-1B")
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("UmbrellaInc/G-Human-1B")
model = AutoModelForCausalLM.from_pretrained("UmbrellaInc/G-Human-1B", device_map="auto")
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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:

# =====================================
# G-Virus.Injector-1B
# Irreversible Cognitive Infection Agent
# =====================================

base_model: WasamiKirua/ProjectHuman-Gemma3-1B
models:
    - model: WasamiKirua/ProjectHuman-Gemma3-1B
    - model: UmbrellaInc/G-Virus.Injector-1B
merge_method: slerp

dtype: bfloat16

parameters:
  t: [0.95, 0.85]
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