Instructions to use antflydb/GLiNER2.5-Decide with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- GLiNER2
How to use antflydb/GLiNER2.5-Decide with GLiNER2:
from gliner2 import AutoExtractor extractor = AutoExtractor.from_pretrained("antflydb/GLiNER2.5-Decide") # Extract entities text = "Apple CEO Tim Cook announced iPhone 15 in Cupertino yesterday." result = extractor.extract_entities(text, ["company", "person", "product", "location"]) print(result) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use antflydb/GLiNER2.5-Decide with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf antflydb/GLiNER2.5-Decide:Q8_0 # Run inference directly in the terminal: llama cli -hf antflydb/GLiNER2.5-Decide:Q8_0
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf antflydb/GLiNER2.5-Decide:Q8_0 # Run inference directly in the terminal: llama cli -hf antflydb/GLiNER2.5-Decide:Q8_0
Build from source code
git clone https://github.com/ggml-org/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-app # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama serve -hf antflydb/GLiNER2.5-Decide:Q8_0 # Run inference directly in the terminal: ./build/bin/llama cli -hf antflydb/GLiNER2.5-Decide:Q8_0
Use Docker
docker model run hf.co/antflydb/GLiNER2.5-Decide:Q8_0
- Llama new
- LM Studio
- Jan
- Ollama
How to use antflydb/GLiNER2.5-Decide with Ollama:
ollama run hf.co/antflydb/GLiNER2.5-Decide:Q8_0
- Unsloth Desktop
- Docker Model Runner
How to use antflydb/GLiNER2.5-Decide with Docker Model Runner:
docker model run hf.co/antflydb/GLiNER2.5-Decide:Q8_0
- Lemonade
How to use antflydb/GLiNER2.5-Decide with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull antflydb/GLiNER2.5-Decide:Q8_0
Run and chat with the model
lemonade run user.GLiNER2.5-Decide-Q8_0
List all available models
lemonade list
- Atomic Chat
|
Download README.md from antflydb/GLiNER2.5-Decide: direct link, hf CLI and curl.
- Browser
- Download file 3.54 kB
-
https://huggingface.co/antflydb/GLiNER2.5-Decide/resolve/main/README.md
- Command line
-
hf download hf://antflydb/GLiNER2.5-Decide/README.md
-
curl -L -o README.md https://huggingface.co/antflydb/GLiNER2.5-Decide/resolve/main/README.md
3.54 kB
| license: apache-2.0 | |
| language: | |
| - en | |
| pipeline_tag: token-classification | |
| base_model: fastino/GLiNER2.5-Decide | |
| tags: | |
| - gliner2 | |
| - gguf | |
| - antfly-inference | |
| - decision-model | |
| ## Canonical Antfly layout (2026-10-17) | |
| This repository follows the upstream Fastino checkpoint name. The previous | |
| `-gguf` repository URL redirects here. The paired filenames identify the | |
| **Q8_0 bundle variant**: the encoder matrices are Q8_0, while the auxiliary | |
| head remains **FP32** despite its `Q8_0` filename suffix. The weight bytes, | |
| tokenizer, and source configuration have not changed. The bundle descriptor | |
| and `antfly_inference_variants.json` name both required components explicitly. | |
| Historical validation reports retain the original paths and measurements; | |
| `gliner_head.gguf` in those reports is now `gliner2-head.Q8_0.gguf`. | |
| This DeBERTa Q8 conversion supports ordinary extraction/classification | |
| compatibility. It does **not** qualify the public typed Decide endpoint: | |
| the exporter strips `decide` and `typed_decisions`. The source checkpoint's | |
| name and the historical browser smoke test do not confer that qualification. | |
| Use a qualified FP32 Decide checkpoint or the separate qualified 1B Q8 bundle | |
| for typed decisions. Native/Metal full-task and long-document qualification | |
| must be established separately for these converted bytes. | |
| # GLiNER2.5 Decide — Antfly Q8_0 split GGUF bundle | |
| This is an Antfly inference bundle converted from [Fastino's GLiNER2.5-Decide](https://huggingface.co/fastino/GLiNER2.5-Decide). The encoder is Q8_0 GGUF; the GLiNER head is a separate GGUF file. The bundle uses Antfly's `gliner2_split_bundle/v1` layout and is intended for Antfly's GLiNER2 inference runtime, including its browser/WASM playground. It is **not** a single-file llama.cpp model. Keep the files and relative paths together. | |
| The source is Apache-2.0 licensed. The local `model.safetensors` used for conversion has SHA-256 `40a5a23ff860dc3dff426cecd1048cacdd29c648c96db209dad818e9686dc997`, matching the file in the [upstream repository](https://huggingface.co/fastino/GLiNER2.5-Decide/tree/main) at revision `5a7adf72a23b4d311abae6ce050d7f0012bb3416`. Model design, intended uses, limitations, and upstream evaluation are described in [Fastino's model card](https://huggingface.co/fastino/GLiNER2.5-Decide). Fastino did not publish this Antfly conversion. | |
| ## Bundle contents | |
| - `antfly_inference_bundle.json` — split-bundle receipt naming the encoder and head. | |
| - `gliner2-encoder.Q8_0.gguf` — quantized encoder, SHA-256 `8d9bea7df21ab4a8a17333f51f246faab5280159e5751ebbadd81a85ec96c871`. | |
| - `gliner2-head.Q8_0.gguf` — GLiNER head, SHA-256 `52cb6197d3dcfe5ad6276ceb037a3333d2921bbcf3dfb8289aeff82fbd5693dc`. | |
| - `config.json`, `encoder_config/config.json`, `special_tokens_map.json`, `tokenizer.json`, `tokenizer_config.json` — configuration and tokenizer files from the source checkpoint. | |
| - `SHA256SUMS` — SHA-256 hashes for all eight bundle files. | |
| Download the repository with `hf download antflydb/GLiNER2.5-Decide --local-dir ./GLiNER2.5-Decide-Q8_0`, then load that directory with an Antfly runtime that supports `gliner2_split_bundle/v1`. For reproducible deployments, pin a repository revision instead of using `main`. | |
| ## Validation | |
| Antfly's focused Decide runtime test passed 3/3 cases with these exact local bundle files and the pinned browser/WASM extraction runtime. This is a compatibility smoke test, not a full quality or cross-browser evaluation. Quantization can change outputs relative to the original checkpoint. | |