File	Size	Description
`model.fp16.onnx`	~5 MB	ONNX header (external data)
`model.fp16.onnx.data`	~1.2 GB	FP16 weights
`tokenizer.json`, `config.json`, `tokenizer_config.json`, `special_tokens_map.json`	small	tokenizer + model config

Conversion

Streaming FP32→FP16 via convert_fp16_streaming.py (bypasses the 2 GB protobuf serialization limit).

Use via fastembed-rs

rust

let embedder = TextEmbedding::try_new(
    InitOptions::new(EmbeddingModel::F2LlmV2_0_6BFp16))?;
let vectors = embedder.embed(vec!["hello world"], None)?;

Pooling: last-token (auto-applied by fastembed-rs). Use the F2LLM instruct format prefix for queries (see the upstream F2LLM repo).

License

Apache 2.0, inherited from the base model.

Provenance and EU AI Act Art. 53 note

Upstream model: codefuse-ai/F2LLM-v2-0.6B — published by codefuse-ai.
Upstream licence: apache-2.0. This repository redistributes under the same terms; it grants no rights the upstream licence does not.
What was done here: format conversion and/or quantisation only (ONNX, F16 precision). No training, no fine-tuning, no merging, no distillation, no change to architecture, vocabulary or capability. Only the numeric representation of the upstream weights differs.
Training data: documented — where it is documented at all — by the upstream provider; see the upstream model card. No training data was used, added or selected by this repository.
Provider status: under Regulation (EU) 2024/1689 the upstream authors remain the provider of this model. Converting the serialisation format does not make this repository the provider of a new general-purpose AI model, and no such claim is made. Questions about training content, copyright policy or model capability belong upstream.

cstr/F2LLM-v2-0.6B-ONNX-FP16

F2LLM-v2-0.6B — FP16 ONNX

Quality

Files

Conversion

Use via fastembed-rs

License

Provenance and EU AI Act Art. 53 note

cstr/
F2LLM-v2-0.6B-ONNX-FP16