Text Classification
Transformers
Safetensors
English
modernbert
commitment-detection
decision-detection
experimental
vela
text-embeddings-inference
Instructions to use TwilightTechie/vela-commitment-classifier-307m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TwilightTechie/vela-commitment-classifier-307m with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="TwilightTechie/vela-commitment-classifier-307m")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("TwilightTechie/vela-commitment-classifier-307m") model = AutoModelForSequenceClassification.from_pretrained("TwilightTechie/vela-commitment-classifier-307m", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Download UPSTREAM_LICENSES.md from TwilightTechie/vela-commitment-classifier-307m: direct link, hf CLI and curl.
- Browser
- Download file 1.62 kB
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https://huggingface.co/TwilightTechie/vela-commitment-classifier-307m/resolve/main/UPSTREAM_LICENSES.md
- Command line
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hf download hf://TwilightTechie/vela-commitment-classifier-307m/UPSTREAM_LICENSES.md
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curl -L -o UPSTREAM_LICENSES.md https://huggingface.co/TwilightTechie/vela-commitment-classifier-307m/resolve/main/UPSTREAM_LICENSES.md
1.62 kB
| # Upstream license declarations and provenance | |
| This distribution contains a fine-tuned derivative of | |
| [`vllm-sr/Vela-1.0-Encoder-307M`](https://huggingface.co/vllm-sr/Vela-1.0-Encoder-307M), | |
| using revision `720ab37904ce15054068d429381bfae7549f00f6`. | |
| That revision's model card declares `license: mit`. Its upstream model is | |
| [`jhu-clsp/mmBERT-base`](https://huggingface.co/jhu-clsp/mmBERT-base), whose queried | |
| model card also declares MIT. | |
| The queried pinned Vela files and upstream mmBERT files provide no separate | |
| LICENSE or NOTICE file. This omission is recorded rather than manufacturing | |
| an upstream copyright notice or assigning ownership of their weights to the | |
| fine-tuning author. The model license file contains the standard MIT permission | |
| and warranty terms, sourced from the | |
| [SPDX MIT license text](https://github.com/spdx/license-list-data/blob/main/text/MIT.txt). | |
| Any authoritative upstream copyright notices subsequently supplied should be | |
| preserved with this distribution. These statements reflect published license | |
| declarations rather than a comprehensive audit of upstream training corpora. | |
| The new classifier head and final two encoder layers were updated in a personal | |
| training experiment. This derivative is not an official upstream release and | |
| does not imply endorsement by vLLM Semantic Router or JHU. | |
| The accompanying reproduction source and synthetic dataset retain Apache-2.0 | |
| licensing from the Semantic Router experiment's source/data context. Their | |
| license copies are separate from the MIT model license. No private reference | |
| document, original test examples or credentials are distributed. | |