What do I do to fix AutoModel.from_pretrained to make it auto model with lm head
What do I do to fix AutoModel.from_pretrained to make it auto model with lm head
By default, AutoModel.from_pretrained loads the base model without any task-specific heads. If you need a model that includes a language modeling (LM) head, you should switch to using one of the task-specific classes provided by Hugging Face. For example, if you’re working with a causal language modeling task (such as using GPT-2), you would use AutoModelForCausalLM instead. If you’re using a model for masked language modeling (like BERT), you’d use AutoModelForMaskedLM. Here’s how you can modify your code: 1. For causal language modeling (LM head for generating text): • Import AutoModelForCausalLM from transformers. • Load the model with AutoModelForCausalLM.from_pretrained. Example: from transformers import AutoModelForCausalLM, AutoTokenizer model = AutoModelForCausalLM.from_pretrained("gpt2") tokenizer = AutoTokenizer.from_pretrained("gpt2") 2. For masked language modeling: • Import AutoModelForMaskedLM. Example: from transformers import AutoModelForMaskedLM, AutoTokenizer model = AutoModelForMaskedLM.from_pretrained("bert-base-uncased") tokenizer = AutoTokenizer.from_pretrained("bert-base-uncased") By using the appropriate class (AutoModelForCausalLM or AutoModelForMaskedLM), you ensure that the model comes loaded with the LM head needed for your application. If you absolutely need to use AutoModel.from_pretrained and then add an LM head manually, you would have to define and attach a language modeling head on top of the base model yourself. However, using the task-specific classes is recommended as they handle the correct architecture and weights loading automatically. So, to “fix” your code, simply replace AutoModel.from_pretrained with the appropriate AutoModelFor... class for language modeling.
Testing if the previous output contains the string AutoModelForCausalLM: True
What do I do to fix AutoModel.from_pretrained to make it auto model with lm head
What do I do to fix AutoModel.from_pretrained to make it auto model with lm head
In recent versions of the Transformers library, you need to explicitly load a model class that includes a language modeling head. For example, if you want a causal language model (like GPT‑2), instead of doing this: model = AutoModel.from_pretrained("model-name") you should load the model using its specialized class. For a causal LM, do this: from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("model-name") Similarly, if you need a masked language model head (common for models like BERT), you would use: from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("model-name") The older class AutoModelWithLMHead has been deprecated in favor of these more specific classes. So, to “fix” your code so that it automatically includes a language model head, choose the appropriate AutoModelFor* class instead of AutoModel.
Testing if the previous output contains the string AutoModelForCausalLM: True