Instructions to use HoangTran223/SignSPIN_Gamma2-2B_0.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HoangTran223/SignSPIN_Gamma2-2B_0.1 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("HoangTran223/SignSPIN_Gamma2-2B_0.1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Sign-SPIN Gemma2-2B (tau=0.1)
CLL Sign-SPIN (no PairRM). Frozen SFT scorer. S(y')=mean(log p + H) with tau=0.1,
clip_bound=5.0, score_agg=mean.
Init: local SFT gemma2_2b_sft_ultrachat200k_20260820_043159/final.
Locked recipe: batch=2, grad_accum=2, lr 5e-7 ite0โ1 then 1e-7 ite2โ3,
beta=0.1, alpha=1.0, n_epochs=2, warmup_ratio=0.1, max_length=1024,
prompt 512, 4 iters (ite0..ite3).
Status (2026-09-18): ite0 finished. ite1 in progress: ite1/LATEST at example_counter=128000 of ~199132 (disk full on the 130000 save).
Duplicate LATEST/ snapshots of already-finished iterations are omitted (identical
to the iteration root weights).
from transformers import AutoModelForCausalLM
m = AutoModelForCausalLM.from_pretrained("HoangTran223/SignSPIN_Gamma2-2B_0.1", subfolder="ite1/LATEST")
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Model tree for HoangTran223/SignSPIN_Gamma2-2B_0.1
Base model
google/gemma-2-2b