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add xpu path for awq (#34712)
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* add xpu path for awq

* update readme
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@jiqing-feng
jiqing-feng authored Nov 15, 2024
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26 changes: 13 additions & 13 deletions docs/source/en/quantization/overview.md
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Expand Up @@ -45,19 +45,19 @@ 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 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) | 🟢 | 🟡 * | 🟢 | 🟡 * | 🔴 ** | 🔴 (soon!) | 4 / 8 | 🟢 | 🟢 | 🟢 | https://github.com/bitsandbytes-foundation/bitsandbytes |
| [compressed-tensors](./compressed_tensors) | 🔴 | 🟢 | 🟢 | 🟢 | 🔴 | 🔴 | 1 - 8 | 🟢 | 🟢 | 🟢 | https://github.com/neuralmagic/compressed-tensors |
| [EETQ](./eetq) | 🟢 | 🔴 | 🟢 | 🔴 | 🔴 | ? | 8 | 🟢 | 🟢 | 🟢 | https://github.com/NetEase-FuXi/EETQ |
| GGUF / GGML (llama.cpp) | 🟢 | 🟢 | 🟢 | 🔴 | 🟢 | 🔴 | 1 - 8 | 🔴 | [See GGUF section](../gguf) | [See GGUF section](../gguf) | https://github.com/ggerganov/llama.cpp |
| [GPTQ](./gptq) | 🔴 | 🔴 | 🟢 | 🟢 | 🔴 | 🔴 | 2 - 3 - 4 - 8 | 🟢 | 🟢 | 🟢 | https://github.com/AutoGPTQ/AutoGPTQ |
| [HQQ](./hqq) | 🟢 | 🟢 | 🟢 | 🔴 | 🔴 | 🟢 | 1 - 8 | 🟢 | 🔴 | 🟢 | https://github.com/mobiusml/hqq/ |
| [Quanto](./quanto) | 🟢 | 🟢 | 🟢 | 🔴 | 🟢 | 🟢 | 2 / 4 / 8 | 🔴 | 🔴 | 🟢 | https://github.com/huggingface/quanto |
| [FBGEMM_FP8](./fbgemm_fp8.md) | 🟢 | 🔴 | 🟢 | 🔴 | 🔴 | 🔴 | 8 | 🔴 | 🟢 | 🟢 | https://github.com/pytorch/FBGEMM |
| [torchao](./torchao.md) | 🟢 | | 🟢 | 🔴 | partial support (int4 weight only) | | 4 / 8 | | 🟢🔴 | 🟢 | https://github.com/pytorch/ao |
| Quantization method | On the fly quantization | CPU | CUDA GPU | RoCm GPU (AMD) | Metal (Apple Silicon) | Intel GPU | 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) | 🟢 | 🟡 * | 🟢 | 🟡 * | 🔴 ** | 🟡 * | 🔴 (soon!) | 4 / 8 | 🟢 | 🟢 | 🟢 | https://github.com/bitsandbytes-foundation/bitsandbytes |
| [compressed-tensors](./compressed_tensors) | 🔴 | 🟢 | 🟢 | 🟢 | 🔴 | 🔴 | 🔴 | 1 - 8 | 🟢 | 🟢 | 🟢 | https://github.com/neuralmagic/compressed-tensors |
| [EETQ](./eetq) | 🟢 | 🔴 | 🟢 | 🔴 | 🔴 | 🔴 | ? | 8 | 🟢 | 🟢 | 🟢 | https://github.com/NetEase-FuXi/EETQ |
| GGUF / GGML (llama.cpp) | 🟢 | 🟢 | 🟢 | 🔴 | 🟢 | 🔴 | 🔴 | 1 - 8 | 🔴 | [See GGUF section](../gguf) | [See GGUF section](../gguf) | https://github.com/ggerganov/llama.cpp |
| [GPTQ](./gptq) | 🔴 | 🔴 | 🟢 | 🟢 | 🔴 | 🔴 | 🔴 | 2 - 3 - 4 - 8 | 🟢 | 🟢 | 🟢 | https://github.com/AutoGPTQ/AutoGPTQ |
| [HQQ](./hqq) | 🟢 | 🟢 | 🟢 | 🔴 | 🔴 | 🔴 | 🟢 | 1 - 8 | 🟢 | 🔴 | 🟢 | https://github.com/mobiusml/hqq/ |
| [Quanto](./quanto) | 🟢 | 🟢 | 🟢 | 🔴 | 🟢 | 🔴 | 🟢 | 2 / 4 / 8 | 🔴 | 🔴 | 🟢 | https://github.com/huggingface/quanto |
| [FBGEMM_FP8](./fbgemm_fp8.md) | 🟢 | 🔴 | 🟢 | 🔴 | 🔴 | 🔴 | 🔴 | 8 | 🔴 | 🟢 | 🟢 | https://github.com/pytorch/FBGEMM |
| [torchao](./torchao.md) | 🟢 | | 🟢 | 🔴 | partial support (int4 weight only) | 🔴 | | 4 / 8 | | 🟢🔴 | 🟢 | https://github.com/pytorch/ao |

<Tip>

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14 changes: 7 additions & 7 deletions src/transformers/quantizers/quantizer_awq.py
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Expand Up @@ -57,14 +57,14 @@ def validate_environment(self, device_map, **kwargs):
raise RuntimeError(
"To use IPEX backend, you need autoawq>0.6.2. Please install the latest version or from source."
)
if (
device_map is not None
and isinstance(device_map, dict)
and (torch.device("cpu") not in device_map.values() or len(device_map.values()) > 1)
):
if device_map is None:
logger.warning_once(
"You have loaded an AWQ model without setting device_map, please set 'cpu' or 'xpu' or 'auto'"
)
elif isinstance(device_map, dict) and "disk" in device_map.values():
raise ValueError(
"You are attempting to load an IPEX version AWQ model with a device_map that contains more than CPU."
" This is not supported. Please make sure only cpu in the device_map."
"You are attempting to load an IPEX version AWQ model with a device_map that contains disk device."
" This is not supported. Please make sure only cpu and xpu in the device_map."
)
else:
if not torch.cuda.is_available():
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