Text Classification
Transformers
Safetensors
English
nli
cross-encoder
qwen3.5
reranker
image-text-to-text
Instructions to use AlexWortega/openjev with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AlexWortega/openjev with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AlexWortega/openjev")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("AlexWortega/openjev", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| # Sync scripts to a remote box and run train + eval there. | |
| # ./run.sh sync # just rsync | |
| # ./run.sh train Qwen/Qwen3.5-0.8B # train (full FT); add --lora --grad-ckpt for 9B via EXTRA | |
| # ./run.sh gen # generate GSM8K candidates via llama-server (background-friendly) | |
| # ./run.sh eval ckpt/qwen3.5-0.8b-nli results/qwen0.8b.json | |
| set -euo pipefail | |
| # override for another box, e.g.: | |
| # HOST=mybox REMOTE=~/qwen_nli PY=python ENVS="HF_HOME=/mnt/hf" ./run.sh train ... | |
| HOST=${HOST:-mybox} | |
| REMOTE=${REMOTE:-~/qwen_nli} | |
| PY=${PY:-python} | |
| ENVS=${ENVS:-} | |
| HERE="$(cd "$(dirname "$0")" && pwd)" | |
| sync() { rsync -az --exclude results --exclude data "$HERE/"{train.py,eval.py,eval_image_nli.py,data_mix.py,run_v2_evals.sh,latent_mlp.py,summarize.py,flappy.py,flappy_video.py,sweep_flappy.sh,doom.py,doom_vision.py,minecraft.py,mc_bot.js,mc_record.js,mc_video.py,hf_publish.py,radar.py,modeling_openjev.py,modeling_qwen35_moe_seqcls.py,webql_bench.py,webql_fulldoc.py,webql_gemini_prompt.py,webql_mlp.py,run.sh} "$HOST:$REMOTE/"; } | |
| case "${1:-}" in | |
| sync) sync ;; | |
| train) | |
| sync | |
| MODEL=${2:-Qwen/Qwen3.5-0.8B}; NAME=$(basename "$MODEL" | tr 'A-Z' 'a-z') | |
| ssh "$HOST" "cd $REMOTE && mkdir -p logs && nohup env $ENVS $PY train.py --model $MODEL --out ckpt/${NAME}-nli ${EXTRA:-} > logs/train_${NAME}.log 2>&1 & echo started pid \$!" | |
| ;; | |
| gen) | |
| sync | |
| ssh "$HOST" "cd $REMOTE && mkdir -p logs data && nohup env $ENVS $PY eval.py --models x --out /dev/null --gen-only > logs/gen_gsm8k.log 2>&1 & echo started pid \$!" | |
| ;; | |
| eval) | |
| sync | |
| CKPT=${2:?ckpt}; OUT=${3:?out} | |
| ssh "$HOST" "cd $REMOTE && mkdir -p logs results && nohup env $ENVS $PY eval.py --models $CKPT dleemiller/ModernCE-large-nli --out $OUT ${EXTRA:-} > logs/eval_$(basename "$OUT" .json).log 2>&1 & echo started pid \$!" | |
| ;; | |
| *) echo "usage: $0 {sync|train MODEL|gen|eval CKPT OUT}"; exit 1 ;; | |
| esac | |