Hercules LLM collection
Collection
Hercules Gemma 3N collection • 6 items • Updated
How to use EpistemeAI/Hercules-gemmaReasoner-3N-it-stem-400 with Transformers:
# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("EpistemeAI/Hercules-gemmaReasoner-3N-it-stem-400", dtype="auto")How to use EpistemeAI/Hercules-gemmaReasoner-3N-it-stem-400 with Unsloth Studio:
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for EpistemeAI/Hercules-gemmaReasoner-3N-it-stem-400 to start chatting
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for EpistemeAI/Hercules-gemmaReasoner-3N-it-stem-400 to start chatting
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for EpistemeAI/Hercules-gemmaReasoner-3N-it-stem-400 to start chatting
pip install unsloth
from unsloth import FastModel
model, tokenizer = FastModel.from_pretrained(
model_name="EpistemeAI/Hercules-gemmaReasoner-3N-it-stem-400",
max_seq_length=2048,
)This finetuned model is specialized in STEM like LCB, CodeForce, AIME24, AIME25, AMC23, MATH500
Note:
This gemma3n model was trained 2x faster with Unsloth and Huggingface's TRL library.