Instructions to use NorviTech/arrmes-functiongemma-270m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use NorviTech/arrmes-functiongemma-270m with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download NorviTech/arrmes-functiongemma-270m --local-dir arrmes-functiongemma-270m
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
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Download README.md from NorviTech/arrmes-functiongemma-270m: direct link, hf CLI and curl.
- Browser
- Download file 1.25 kB
-
https://huggingface.co/NorviTech/arrmes-functiongemma-270m/resolve/main/README.md
- Command line
-
hf download hf://NorviTech/arrmes-functiongemma-270m/README.md
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curl -L -o README.md https://huggingface.co/NorviTech/arrmes-functiongemma-270m/resolve/main/README.md
1.25 kB
metadata
license: gemma
base_model: google/functiongemma-270m-it
tags:
- mlx
- lora
- functiongemma
- tool-calling
- arrmes
Arrmes FunctionGemma-270M v9 Residual FP16 QLoRA Adapter (v1.6.0)
Unassisted residual FP16 LoRA adapter over the 4-bit FunctionGemma-270M base (183.1 MiB total footprint), subject to the Gemma Terms of Use (GEMMA_TERMS_NOTICE.txt).
Artifact & Unassisted Benchmark Summary (LocalModel, backend="mlx-lm")
v9/adapters.safetensorsSHA-256:a0337f083c362d66f406129d0ee6f4661597055bd51772233241c0e2690cf124- Template-Disjoint
acceptance-v7v2Positives (N=150): Track A Raw126/150(84.0%), Track B Verified135/150(90.0%, Wilson 95% LB84.16%) - Template-Disjoint
acceptance-v7Hard Negatives (N=150): Track A Raw49/150(32.67%), Track B Verified133/150(88.67%, Wilson 95% LB82.60%) - Frozen
overnight-v1(N=80): Track A Raw59/80(73.75%), Track B Verified69/80(86.25%) - Apple M4 Pro Metal Warm Latency:
p50 = 110.08 ms,p95 = 124.80 ms(183.1 MiBcombined 4-bit base + FP16 LoRA footprint).
