AISA-AR-FunctionCall-FT safetensors download | Hugging Bay

Q: What is this model?

AISA-Framework/AISA-AR-FunctionCall-FT is an open-weights language model for text generation published by AISA-Framework, added to Hugging Bay Jun 30, 2026. Model from Hugging Face for text generation: AISA-Framework/AISA-AR-FunctionCall-FT · transformers

Q: Can I use it commercially?

It is released under the apache-2.0 license. Commercial use is allowed. Permissive open license: commercial use, modification, and redistribution are permitted.

Q: How big is it?

Hosted here: 10 files, 575.5 MB. Full repo upstream: 575.5 MB. The recommended download, model.safetensors, is 536.2 MB.

Q: What can I download here?

Hosted here: 10 files, 575.5 MB. Full repo upstream: 575.5 MB. The original release is at https://huggingface.co/AISA-Framework/AISA-AR-FunctionCall-FT.

Q: File pattern scans

Automated file-pattern scans flagged nothing; not a safety guarantee. 10 hosted files carry a published SHA-256 you can re-hash. The machine-readable verdict is at /api/artifacts/hf-model-aisa-framework-aisa-ar-functioncall-ft/safety on Hugging Bay.

Q: Will AISA-Framework/AISA-AR-FunctionCall-FT run on my computer?

We can’t check the fit; we don’t know your machine. We don’t have your machine’s specs, so no check ran and no verdict is shown. Answer two quick questions and we’ll estimate, from the memory you tell us, whether it fits your machine. Or skip it; you can still download; fit isn’t checked.

AISA-Framework

AISA-AR-FunctionCall-FT

AISA-Framework/AISA-AR-FunctionCall-FT

Model details

text generationLicense: apache-2.0SHA-256 recorded for 10 of 11 filessafetensors

Content controls: not assessed.

Listed for producing tool call requests; for developers evaluating tool integrations. Catalog sources: license, cardMetadata.license, baseModel, tags, task, cardMetadata.pipelineTag.

View as JSON →

Your next step

Use it from code

This Python snippet downloads the selected file. Running the model needs its own library and setup.

from urllib.request import urlretrieve

urlretrieve(
    "https://huggingbay.xyz/api/downloads/hf-model-aisa-framework-aisa-ar-functioncall-ft/model.safetensors",
    "model.safetensors",
)

Other ways

Run it on your computerOpen in Hugging Bay appSend to a computerApp links support one GGUF file.

10 hosted of 11 listed · Hashes recorded. Date not recorded.

Selected downloadmodel.safetensors536 MB · 1 file Download · 536 MB (1 file)

Open-file help

Content controls: not assessed.

Check your download →

Compare your file’s SHA-256 with the recorded hash.

10 hosted of 11 listed

Hashes recorded. Date not recorded.

File	Tamanho	SHA-256	Origem	Baixar
Weights
`model.safetensors` Default	536.2 MB	`8c4c66a0…b398a12d` `8c4c66a0a15f50c7959e1fbb140f05544b520b89ab842340fecfc79fb398a12d`	Hosted	Baixar
Tokenizer & config
`added_tokens.json`	63 bytes	`52233b28…51d97153` `52233b287bd11f2f03d19fb9823e15698d9d55a811e2cce8f02bae2551d97153`	Hosted	Baixar
`chat_template.jinja`	13.9 KB	`0dbaf708…b9dd604a` `0dbaf70819c970c9bacd7125be8e9db46b7bc0e6ed3bc303d92bd58fb9dd604a`	Hosted	Baixar
`config.json`	1.4 KB	`f0d5bc4e…b3200bc5` `f0d5bc4e2c43a007aff3e58cc339e82f1b233317616a1c0bb79edc4cb3200bc5`	Hosted	Baixar
`generation_config.json`	205 bytes	`a932a4dd…8a8f348d` `a932a4dddbcfd2902e17ac185b802e2c661b216cd914463c0cf9e9418a8f348d`	Hosted	Baixar
`special_tokens_map.json`	714 bytes	`8108fc6f…84df3c13` `8108fc6fd7cfcd699c376de8ec30d0e117a915f6a03f20e04a4c3b6a84df3c13`	Hosted	Baixar
`tokenizer.json`	33.4 MB	`b6b09a0b…27d41fb2` `b6b09a0b4a803ad453063ca4bb49a784540e8120004e2450e025df2b27d41fb2`	Hosted	Baixar
`tokenizer.model`	4.69 MB	`aa009fcb…7a50ceb3` `aa009fcbc3589a9904d30d04834094fea4653c2ac6d2de2cd1262d4f7a50ceb3`	Hosted	Baixar
`tokenizer_config.json`	1.16 MB	`7a6b96e6…47cdfa76` `7a6b96e6b29716d881aaa12daabb227e9e17f50a2f4c1fb83f62a2c847cdfa76`	Hosted	Baixar
Docs
`.gitattributes`	1.57 KB	—	Upstream only	File metadata
`README.md`	5.96 KB	`ed469522…5fa6c326` `ed4695226a3c9728c591607bc5653276663cc503c183ed99f89f16e85fa6c326`	Hosted	Baixar

Verificar um download

In the folder where you saved model.safetensors, run:

macOS

shasum -a 256 -- 'model.safetensors'

Linux

sha256sum -- 'model.safetensors'

Windows

Get-FileHash -LiteralPath 'model.safetensors' -Algorithm SHA256

Compare the result with the recorded SHA-256.

AISA-AR-FunctionCall-FT

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