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Source - BertTokenizer
- Wrapper around HuggingFace tokenizer configured for BERT-style encoding.
- ImageModelInfo
- Metadata for an image embedding model.
- ModelInfo
- Metadata for an embedding model.
- RlxBertModel
- RLX-compiled BERT model ready for inference.
- RlxEmbed
- High-level embedding model — auto-detects BERT / NomicBERT / NomicVision.
- RlxNomicModel
- RLX-compiled NomicBERT with shape-bucketed compile cache.
- RlxVisionModel
- RLX-compiled NomicVision encoder (patch preprocess host-side, trunk on RLX).
- TokenizedBatch
- Output of batch tokenization: token IDs, attention masks, and token type IDs.
- Arch
- Detected embedding architecture from
config.json. - EmbeddingModel
- Supported text embedding models.
- ImageEmbeddingModel
- Supported image embedding models.
- ModelArch
- Model architecture type.
- Pooling
- Pooling strategy for reducing token hidden states to one vector per sequence.
- assemble_vision_hidden
- Assemble encoder input
[batch, seq, hidden] from NCHW pixels + preprocess weights. - compile_model
- Compile an embedding graph for the given batch/seq on
device. - compile_model_cpu
- Compile on CPU (convenience for tests and default
RlxEmbed::from_dir). - default_pooling
- Default pooling heuristic from HuggingFace repo id.
- detect_arch
- Detect architecture from config.json fields.
- embed_with_rlx
- Embed texts with a compiled BERT model: tokenize, forward, pool, L2-normalize.
- l2_normalize_in_place
- L2-normalize a vector in place (matches fastembed: divide by norm + 1e-12).
- models_map
- Get the global model registry.
- pool_embeddings
- Pool
[batch, seq, hidden] hidden states into [batch, hidden] and L2-normalize.