Phi-3.5-mini

About

What Phi-3.5-mini is

🎉Phi-4: [multimodal-instruct | onnx]; [mini-instruct | onnx] Model Summary Phi-3.5-mini is a lightweight, state-of-the-art open model built upon datasets used for Phi-3 - synthetic data and filtered publicly available websites - with a focus on very high-quality, reasoning dense data. The model belongs to the Phi-3 model family and supports 128K token context length. The model underwent a rigorous enhancement process, incorporating both supervised fine-tuning, proximal policy optimization, and direct preference optimization to ensure precise instruction adherence and robust safety measures. 🏡 Phi-3 Portal <br 📰 Phi-3 Microsoft Blog <br 📖 Phi-3 Technical Report <br 👩‍🍳 Phi-3 Cookbook <br 🖥️ Try It <br Phi-3.5: [mini-instruct | onnx]; [[MoE-instruct]](https://huggingface.co/microsoft/Phi-3.5-MoE-instruct); [[vision-instruct]](https://huggingface.co/microsoft/Phi-3.5-vision-instruct) Intended Uses Primary Use Cases The model is intended for commercial and research use in multiple languages. The model provides uses for general purpose AI systems and applications which require: 1) Memory/compute constrained environments 2) Latency bound scenarios 3) Strong reasoning (especially code, math and logic) Our model is designed to accelerate research on language and multimodal models, for use as a building block for generative AI powered features. Use Case Considerations Our models are not specifically designed or evaluated for all downstream purposes. Developers should consider common limitations of language models as they select use cases, and evaluate and mitigate for accuracy, safety, and fariness before using within a specific downstream use case, particularly for high risk scenarios. Developers should be aware of and adhere to applicable laws or regulations (including privacy, trade compliance laws, etc.) that are relevant to their use case. Nothing contained in this Model Card should be interpreted as or deemed a restriction or modification to the license the model is released under. Release Notes This is an update over the June 2024 instruction-tuned Phi-3 Mini release based on valuable user feedback. The model used additional post-training data leading to substanti

Summarised from the published model card. Read the full card on the HuggingFace links below.

Specifications

What it is

How it works

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Variants

Sizes & precisions

Open weights ship in several sizes and precisions. One page, all the variants — pick the one that fits your GPU. VRAM figures are estimates from model size.

Using it via the API

Call it like any OpenAI endpoint

Once AxForge deploys phi-3-5-mini for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (phi-3-5-mini below is illustrative; you get the exact model name on deployment.)

$ curl -sS https://api.axforge.ai/v1/chat/completions \
  -H "Authorization: Bearer $AXFORGE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"phi-3-5-mini","messages":[{"role":"user","content":"Hello"}]}'

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Open weights

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