@@ -54,8 +54,8 @@ For each model type, there is a separate class for each machine learning framewo
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from transformers import AutoModelForCausalLM, MistralForCausalLM
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# load with AutoClass or model-specific class
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model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-7B-v0.1", , torch_dtype="auto", device_map="auto")
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model = MistralForCausalLM.from_pretrained("mistralai/Mistral-7B-v0.1", , torch_dtype="auto", device_map="auto")
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model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-7B-v0.1", torch_dtype="auto", device_map="auto")
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model = MistralForCausalLM.from_pretrained("mistralai/Mistral-7B-v0.1", torch_dtype="auto", device_map="auto")
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```
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</hfoption>
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@@ -272,6 +272,7 @@ Explicitly set the [torch_dtype](https://pytorch.org/docs/stable/tensor_attribut
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<hfoption id="specific dtype">
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||||
```py
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import torch
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from transformers import AutoModelForCausalLM
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gemma = AutoModelForCausalLM.from_pretrained("google/gemma-7b", torch_dtype=torch.float16)
|
||||
|
||||
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