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danielfein/raid-dual-neologism-tokens
raid-dual-neologism-tokens is a text generation model from danielfein. Use it when you need the model to write or continue text. It is set up for pytorch. The card lists the license as mit.
This repo contains two learned token embeddings trained on matched RAID GPT-4 vs human text pairs.
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Updated Mar 17, 2026
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From the Hugging Face model README
This repo contains two learned token embeddings trained on matched RAID GPT-4 vs human text pairs.
Tokens:
<neo_detect_ai_900001><neo_detect_human_900002>Artifacts:
concept_900001_token.pt: AI-style token checkpointconcept_900002_token.pt: human-style token checkpointraid_eval_summary.json: held-out RAID dual-token evaluationbeemo_eval_summary.json: cross-dataset transfer evaluation on Beemo model outputsThe checkpoints are small PyTorch payloads with keys:
concept_idnew_tokennew_token_idembeddingimport torch
payload = torch.load('concept_900001_token.pt', map_location='cpu')
token = payload['new_token']
embedding = payload['embedding']
These are not full finetuned model weights. They are learned embedding rows intended to be inserted into the base tokenizer/model vocabulary used during training.
Repo: danielfein/raid-dual-neologism-tokens