Text Classification
PEFT
Safetensors
English
decision-model
calibration
lora
multiple-choice
typesafe
gemma4
kev
Eval Results (legacy)
Instructions to use JohnP1/kev-gemma4-e2b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use JohnP1/kev-gemma4-e2b with PEFT:
from peft import PeftModel from transformers import AutoModel base_model = AutoModel.from_pretrained("google/gemma-4-E2B") model = PeftModel.from_pretrained(base_model, "JohnP1/kev-gemma4-e2b") - Notebooks
- Google Colab
- Kaggle
Download provenance.json from JohnP1/kev-gemma4-e2b: direct link, hf CLI and curl.
- Browser
- Download file 6.51 kB
-
https://huggingface.co/JohnP1/kev-gemma4-e2b/resolve/main/provenance.json
- Command line
-
hf download hf://JohnP1/kev-gemma4-e2b/provenance.json
-
curl -L -o provenance.json https://huggingface.co/JohnP1/kev-gemma4-e2b/resolve/main/provenance.json
6.51 kB
| { | |
| "config": { | |
| "base": "google/gemma-4-E2B", | |
| "base_revision": "d29ff6b45f081a49ee2733a859c9c9c2d95d1a6f", | |
| "seed": 0, | |
| "epochs": 1, | |
| "lr": 0.0001, | |
| "batch": 4, | |
| "accum": 2, | |
| "dtype": "bf16", | |
| "weights_dtype": "bf16", | |
| "checkpointing": 1, | |
| "p_none_pair": 0.25 | |
| }, | |
| "config_sha256": "355241763405ebfaa97b051898d14a98695c5ef0ed47b6877082fca47adf1506", | |
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| "platform": "HF Jobs l4x1 (job 6ab426ec52d0dbd7f1d86bac)", | |
| "torch": "2.8.0+cu128", | |
| "device": "cuda", | |
| "gpu": "NVIDIA L4", | |
| "legacy_checkpoint": false, | |
| "measured_checkpoint": { | |
| "requested": "runs/g4-e2b-e1-fp32/00-trial-0/checkpoint", | |
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| "adapter_sha256": "93a489ba6fd4eddb766e9f9bbd70fbec04babe33c7ecd3925f5f9973e325410a", | |
| "inference_temperature": 1.0 | |
| }, | |
| "eval_device": "mps", | |
| "resumed_evaluation": true, | |
| "resumed_source_hashes": { | |
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