Feature Extraction
Transformers
Safetensors
English
cronformer
cron
schedules
text-to-cron
structured-prediction
custom-code
custom_code
Eval Results (legacy)
Instructions to use impalasys/cronformer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use impalasys/cronformer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="impalasys/cronformer", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("impalasys/cronformer", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 1,129 Bytes
69c05ab | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 | {
"repo_id": "impalasys/cronformer",
"release": "v0.1.0",
"source_checkpoint": "/Users/shukant/Library/CloudStorage/GoogleDrive-sukantk3.4@gmail.com/My Drive/Checkpoints/Codex/Cronformer/passes/pass322-full-broad-failure-repair-v1/checkpoint/num_steps-12000",
"release_dir": "/Users/shukant/Library/CloudStorage/GoogleDrive-sukantk3.4@gmail.com/My Drive/Checkpoints/Cronformer/hf_releases/impalasys-cronformer-v0.1.0",
"checkpoint_pass": "pass322-full-broad-failure-repair-v1",
"checkpoint_step": "num_steps-12000",
"files_expected": [
"MANIFEST.json",
"README.md",
"RELEASE.json",
"SHA256SUMS",
"__init__.py",
"config.json",
"configuration_cronformer.py",
"cron.py",
"model.safetensors",
"modeling_cronformer.py",
"special_tokens_map.json",
"tokenizer_config.json",
"vocab.txt"
],
"validation_status": "passed",
"validation_command": "bazel run //uncommonstash/cronformer:validate_hf_cronformer_release -- --hf-dir <release-dir> --local-files-only --json",
"parameters": 6334826,
"model_safetensors_bytes": 25368616,
"model_safetensors_mib": 24.19
}
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