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FIX / Docs: Minor changes in quantization docs (#30985)

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* Change in quantization docs

* Update overview.md

* Update docs/source/en/quantization/overview.md

Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>

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Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
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docs/source/en/quantization/overview.md
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@ -24,14 +24,14 @@ Interested in adding a new quantization method to Transformers? Read the [HfQuan
</Tip>
> [!TIP]
> If you are new to the quantization field, we recommend you to check out these beginner-friendly courses about quantization
> in colaboration with DeepLearning.AI:
<Tip>
> - [Quantization Fundamentals with Hugging Face](https://www.deeplearning.ai/short-courses/quantization-fundamentals-with-hugging-face/)
If you are new to the quantization field, we recommend you to check out these beginner-friendly courses about quantization in collaboration with DeepLearning.AI:
> - [Quantization in Depth](https://www.deeplearning.ai/short-courses/quantization-in-depth/)
* [Quantization Fundamentals with Hugging Face](https://www.deeplearning.ai/short-courses/quantization-fundamentals-with-hugging-face/)
* [Quantization in Depth](https://www.deeplearning.ai/short-courses/quantization-in-depth/)
</Tip>
## When to use what?
@ -45,14 +45,14 @@ In short, supporting a wide range of quantization methods allows you to pick the
Use the table below to help you decide which quantization method to use.
| Quantization method | On the fly quantization | CPU | CUDA GPU | RoCm GPU (AMD) | Metal (Apple Silicon) | torch.compile() support | Number of bits | Supports fine-tuning (through PEFT) | Serializable | 🤗 transformers support | Link to library |
| Quantization method | On the fly quantization | CPU | CUDA GPU | RoCm GPU (AMD) | Metal (Apple Silicon) | torch.compile() support | Number of bits | Supports fine-tuning (through PEFT) | Serializable with 🤗 transformers | 🤗 transformers support | Link to library |
|-------------------------------------|-------------------------|-----|----------|----------------|-----------------------|-------------------------|----------------|-------------------------------------|--------------|------------------------|---------------------------------------------|
| [AQLM](./aqlm) | 🔴 | 🟢 | 🟢 | 🔴 | 🔴 | ? | 1 / 2 | 🟢 | 🟢 | 🟢 | https://github.com/Vahe1994/AQLM |
| [AWQ](./awq) | 🔴 | 🔴 | 🟢 | 🟢 | 🔴 | ? | 4 | 🟢 | 🟢 | 🟢 | https://github.com/casper-hansen/AutoAWQ |
| [bitsandbytes](./bitsandbytes) | 🟢 | 🔴 | 🟢 | 🔴 | 🔴 | 🔴 | 4 / 8 | 🟢 | 🟢 | 🟢 | https://github.com/TimDettmers/bitsandbytes |
| [EETQ](./eetq) | 🟢 | 🔴 | 🟢 | 🔴 | 🔴 | ? | 8 | 🟢 | 🟢 | 🟢 | https://github.com/NetEase-FuXi/EETQ |
| GGUF / GGML (llama.cpp) | 🟢 | 🟢 | 🟢 | 🔴 | 🟢 | 🔴 | 1 - 8 | 🔴 | 🟢 | [See GGUF section](../gguf) | https://github.com/ggerganov/llama.cpp |
| GGUF / GGML (llama.cpp) | 🟢 | 🟢 | 🟢 | 🔴 | 🟢 | 🔴 | 1 - 8 | 🔴 | [See GGUF section](../gguf) | [See GGUF section](../gguf) | https://github.com/ggerganov/llama.cpp |
| [GPTQ](./gptq) | 🔴 | 🔴 | 🟢 | 🟢 | 🔴 | 🔴 | 4 / 8 | 🟢 | 🟢 | 🟢 | https://github.com/AutoGPTQ/AutoGPTQ |
| [HQQ](./hqq) | 🟢 | 🔴 | 🟢 | 🔴 | 🔴 | 🟢 | 1 - 8 | 🟢 | 🔴 | 🟢 | https://github.com/mobiusml/hqq/ |
| [HQQ](./hqq) | 🟢 | 🟢 | 🟢 | 🔴 | 🔴 | 🟢 | 1 - 8 | 🟢 | 🔴 | 🟢 | https://github.com/mobiusml/hqq/ |
| [Quanto](./quanto) | 🟢 | 🟢 | 🟢 | 🔴 | 🟢 | 🟢 | 2 / 4 / 8 | 🔴 | 🔴 | 🟢 | https://github.com/huggingface/quanto |