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champ

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@@ -32,23 +32,24 @@ Now, you can create the pipeline, automatically pulling the weights from this re
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  ```py
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  from champ import CHAMPPipeline
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- pipeline = CHAMPPipeline.from_pretrained(
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- "benjamin-paine/champ",
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- torch_dtype=torch.float16,
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- variant="fp16",
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- device="cuda",
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- ).to("cuda", dtype=torch.float16)
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  ```
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  Or, as a single file:
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  ```py
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- pipeline = CHAMPPipeline.from_pretrained(
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- "benjamin-paine/champ",
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- torch_dtype=torch.float16,
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- variant="fp16",
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- device="cuda",
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- ).to("cuda", dtype=torch.float16)
 
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  ```
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  Follow this format for execution:
 
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  ```py
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  from champ import CHAMPPipeline
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+ pipeline = CHAMPPipeline.from_pretrained(
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+ "benjamin-paine/champ",
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+ torch_dtype=torch.float16,
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+ variant="fp16",
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+ device="cuda",
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+ ).to("cuda", dtype=torch.float16)
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  ```
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  Or, as a single file:
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  ```py
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+ from champ import CHAMPPipeline
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+ pipeline = CHAMPPipeline.from_single_file(
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+ "benjamin-paine/champ",
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+ torch_dtype=torch.float16,
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+ variant="fp16",
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+ device="cuda",
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+ ).to("cuda", dtype=torch.float16)
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  ```
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  Follow this format for execution: