Instructions to use YuCollection/gemma-4-31B-it-assistant-bf16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use YuCollection/gemma-4-31B-it-assistant-bf16 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("YuCollection/gemma-4-31B-it-assistant-bf16") model = AutoModelForCausalLM.from_pretrained("YuCollection/gemma-4-31B-it-assistant-bf16") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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@@ -5,17 +5,32 @@ license_link: https://ai.google.dev/gemma/docs/gemma_4_license
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pipeline_tag: any-to-any
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</p>
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> [!Note]
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pipeline_tag: any-to-any
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> **Note:** This repository is an **archived mirror** and is **not** the original upstream source.
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> The original model, weights, and documentation are developed and maintained by **Google DeepMind**.
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> All hosted model weights are **unmodified**.
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> The model is released under the **Apache License, Version 2.0**, which permits use, modification, and redistribution under its terms.
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> *This repository is not affiliated with, endorsed by, or sponsored by Google DeepMind.*
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<p align="center">
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<a href="https://huggingface.co/collections/google/gemma-4" target="_blank">
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<img src="https://img.shields.io/badge/Hugging%20Face-Models-yellow?style=flat-square">
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</a>
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<a href="https://github.com/google-gemma" target="_blank">
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<img src="https://img.shields.io/badge/GitHub-Source-181717?style=flat-square">
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</a>
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<a href="https://ai.google.dev/gemma/docs/mtp/mtp" target="_blank">
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<img src="https://img.shields.io/badge/MTP-Documentation-0A66C2?style=flat-square">
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</a>
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<br>
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<a href="https://ai.google.dev/gemma/docs/gemma_4_license" target="_blank">
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<img src="https://img.shields.io/badge/License-Apache%202.0-red?style=flat-square">
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</a>
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<a href="https://deepmind.google/models/gemma/" target="_blank">
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<img src="https://img.shields.io/badge/Authors-Google%20DeepMind-blue?style=flat-square">
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</a>
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</p>
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> [!Note]
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