Text Classification
Transformers
ONNX
Safetensors
English
roberta
editlens
ai-detection
quantization
local-inference
text-embeddings-inference
Instructions to use CoderBak/editlens_roberta_modelkit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CoderBak/editlens_roberta_modelkit with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="CoderBak/editlens_roberta_modelkit")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("CoderBak/editlens_roberta_modelkit") model = AutoModelForSequenceClassification.from_pretrained("CoderBak/editlens_roberta_modelkit", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "schema_version": 1, | |
| "repository": "CoderBak/editlens_roberta_modelkit", | |
| "license": "CC-BY-NC-SA-4.0", | |
| "public": true, | |
| "gated": false, | |
| "source_repository": "pangram/editlens_roberta-large", | |
| "source_revision": "f93e1ace74528cfb48f337ab2fe946fb71a728cb", | |
| "original_weights": { | |
| "path": "model.safetensors", | |
| "precision": "float32", | |
| "size_bytes": 1421503560, | |
| "sha256": "869f33df7928c447bbd150d3b5192b4ea90b1cbd2ee4aad97f5d51d59dfc8cfb", | |
| "unchanged_from_upstream": true | |
| }, | |
| "generated_utc": "2026-09-20T10:24:59.474264+00:00", | |
| "build_environment": { | |
| "python": "3.13.0", | |
| "os": "Darwin", | |
| "os_version": "27.2", | |
| "architecture": "arm64", | |
| "packages": { | |
| "torch": "2.14.0", | |
| "transformers": "5.17.0", | |
| "tokenizers": "0.23.2", | |
| "huggingface-hub": "1.31.0", | |
| "safetensors": "0.8.0", | |
| "numpy": "2.5.3", | |
| "onnx": "1.23.0", | |
| "onnxruntime": "1.30.0", | |
| "onnxconverter-common": "1.16.0", | |
| "protobuf": "7.36.2", | |
| "ml-dtypes": "0.6.0" | |
| } | |
| }, | |
| "maximum_sequence_tokens_including_special_tokens": 512, | |
| "num_labels": 4, | |
| "default_variant": "fp32", | |
| "variants": [ | |
| { | |
| "id": "fp32", | |
| "path": "onnx/model.onnx", | |
| "recommended_default": true, | |
| "auto_select": true, | |
| "status": "numerical-smoke-tests-passed", | |
| "size_bytes": 1421900913, | |
| "sha256": "ddd1173f2ef517ad499965e5029fae8099a8054a2bc76d8134e5889cc4ed1b3e", | |
| "opsets": { | |
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| "external_tensor_files": [], | |
| "validated_provider": "CPUExecutionProvider", | |
| "numerical_check_passed": true, | |
| "validation_report": "validation/fp32.json", | |
| "accuracy_evaluated": false, | |
| "accelerator_execution_tested": false | |
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| { | |
| "id": "fp16", | |
| "path": "onnx/model_fp16.onnx", | |
| "recommended_default": false, | |
| "auto_select": false, | |
| "status": "numerical-smoke-tests-passed", | |
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| "validation_report": "validation/fp16.json", | |
| "accuracy_evaluated": false, | |
| "accelerator_execution_tested": false | |
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| { | |
| "id": "int8", | |
| "path": "onnx/model_int8.onnx", | |
| "recommended_default": false, | |
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| "limitations": [ | |
| "Numerical conversion checks only; no labeled accuracy benchmark.", | |
| "INT8 is experimental and failed the documented numerical acceptance gate.", | |
| "No cross-platform or accelerated-provider compatibility certification.", | |
| "Checksums establish file integrity; they are not an independent publisher signature." | |
| ] | |
| } | |