Text Classification
PEFT
Safetensors
English
decision-model
calibration
lora
multiple-choice
typesafe
qwen3.5
Eval Results (legacy)
Instructions to use jaredpalmer/kev-0.8b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use jaredpalmer/kev-0.8b with PEFT:
from peft import PeftModel from transformers import AutoModel base_model = AutoModel.from_pretrained("Qwen/Qwen3.5-0.8B-Base") model = PeftModel.from_pretrained(base_model, "jaredpalmer/kev-0.8b") - Notebooks
- Google Colab
- Kaggle
Kev-0.8B: dates+unknowable delta (locked test 0.834 / 0.684); previous weights at tag v7-base
2256796 verified Download provenance.json from jaredpalmer/kev-0.8b: direct link, hf CLI and curl.
- Browser
- Download file 3.12 kB
-
https://huggingface.co/jaredpalmer/kev-0.8b/resolve/54f4f8777356cd5bbbb6c6919c657f26e6f2f6d8/provenance.json
- Command line
-
hf download hf://jaredpalmer/kev-0.8b@54f4f8777356cd5bbbb6c6919c657f26e6f2f6d8/provenance.json
-
curl -L -o provenance.json https://huggingface.co/jaredpalmer/kev-0.8b/resolve/54f4f8777356cd5bbbb6c6919c657f26e6f2f6d8/provenance.json
3.12 kB
| { | |
| "config": { | |
| "epochs": 1, | |
| "seed": 1, | |
| "lr": 4e-05, | |
| "lora": 16, | |
| "accum": 1, | |
| "batch": 8, | |
| "perm_kl": 0.0, | |
| "perm_frac": 0.3, | |
| "ord_w": 0.0, | |
| "p_none": 0.1, | |
| "p_none_distract": 0.12, | |
| "p_distract": 0.15, | |
| "p_none_pair": 0.25, | |
| "synthetic_repeat": 1, | |
| "public_frac": 1.0, | |
| "head_lr": 0.0, | |
| "weight_decay": 0.01, | |
| "anchor_w": 0.0, | |
| "dtype": "bf16", | |
| "replay": 2000, | |
| "base": "Qwen/Qwen3.5-0.8B-Base", | |
| "base_revision": "dc7cdfe2ee4154fa7e30f5b51ca41bfa40174e68", | |
| "init_from": "jaredpalmer/kev-0.8b", | |
| "data": "evals/night2/dates_unknowable.jsonl" | |
| }, | |
| "config_sha256": "0e130e9f338c8a4c911c6dc37493b36e6be7ca972cbafbb42466043b6daa7a4b", | |
| "suite_sha256": "a8f50e481b7d90b97da049e0ff6a01cee2f1ed204aed61a8265af0edbb5514d2", | |
| "source_hashes": { | |
| "kev/__init__.py": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855", | |
| "kev/anchors.py": "089d8a5493502bb26f540eb1c5e681780ca0bb01276073d4e1733211f15d0e10", | |
| "kev/api.py": "c9eebbdb6c625563d33f030299ce0fbe8b50493dd1e92592df9514c30f5720af", | |
| "kev/autoresearch.py": "0a8aa6b57c1c9ba93d25b2cf631b03aed2e686e374c1148002eec48765b7b1fc", | |
| "kev/benchmark.py": "4192ec3b26b065452f84bde38a091e6854a28fe185d2e0f39a0c91b2efe69df7", | |
| "kev/compare.py": "bd0445f021de59e35c7bff9304e39dd2e1211e3877a453575594ae7b81b0ada4", | |
| "kev/composition.py": "f335ed17e18e0a544893db5e22b9a059e6ce1b2e14dbb863ac7d7bbf8f3e0536", | |
| "kev/contrastive.py": "cbb979aa5d40265ad0e64695f94b281d91751fa405811ddfa8212fede111edcf", | |
| "kev/data.py": "997c31d737c2a130ade49edd6534aa47d910786c98af883745b1a97ec858a704", | |
| "kev/evaluate.py": "1b20e3f9edf417aa8dae924b1526e52f74b710cadf7213c5ec68334f6e7f8fe1", | |
| "kev/experiment.py": "ba034856f79bd500d8b2eeeb7382e4db3fccb30b437f9f3cf55cf1a7c565a6c9", | |
| "kev/jev.py": "e0213782359ba2f95adbf045ddaf0a008b08b4162bf6a9b66d4ce55fc91a51cb", | |
| "kev/model.py": "a17d57a52da3fe6ebef7146ce548bd3cedc09e21cc2b7738d9077771f5f16989", | |
| "kev/plot.py": "d689c7dd18cde7f9ea77cb4f55c50ff7da1880b21cb2ecf244348e45842a1382", | |
| "kev/publish.py": "8f23cda767008756e0f169249eb44577db76bd6c1e12e9cf64c302bad04c8f16", | |
| "kev/serve.py": "d095bbee3a210fa8807d1a7b073b56181c93aa69b00f2e243a323ab0a19fa8c9", | |
| "kev/study_v3.py": "9fc44d44dad09a4f1ee29a7bcb2eb3c7aa373d09186d0e9533666b69ec95c401", | |
| "kev/suite.py": "44858f9a99df086a47d1ae36141631fab6fb6a8293a9e1d0c6ad397ddcfaf94a", | |
| "kev/train.py": "c2a3770072b73dd4c0769c8f188ddedbb402f2f8195df6e10b11e5112cab734b", | |
| "kev/transfer_v9.py": "588aa2ff3ec0823c2e31733bef9a3748b263849c966ef6a80ebd686539c605e9", | |
| "modal_app.py": "d3700b2914be5ef6baa6d588a967d3a242903e1ed96d0f5cc525a8908aa58340", | |
| "pyproject.toml": "52da5eea3efc6f2b1c0589acebad62e56a214294bb02c1a4218c93efd4af3182", | |
| "uv.lock": "18b3e5ea0f25d2e8546fab81f16cb965ae05c3289fffaaa1ce27d114adee47f3" | |
| }, | |
| "git_commit": "19dcae9b6e3e1a48200c5825aad9fc200d31e20a", | |
| "platform": "Linux-4.19.0-gvisor-x86_64-with-glibc2.36", | |
| "torch": "2.8.0+cu128", | |
| "device": "cuda", | |
| "gpu": "NVIDIA H100 80GB HBM3", | |
| "legacy_checkpoint": false | |
| } | |