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docs: update usage example
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README.md
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@@ -45,21 +45,45 @@ pip install -v --disable-pip-version-check --no-cache-dir --global-option="--cpp
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## Examples
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###
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```python
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from transformers import AutoTokenizer,
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tokenizer = AutoTokenizer.from_pretrained('AIRI-Institute/gena-lm-bigbird-base-sparse')
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model =
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```
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### How to load the model to fine-tune it on classification task
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```python
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from
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tokenizer = AutoTokenizer.from_pretrained('AIRI-Institute/gena-lm-bigbird-base-sparse')
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model =
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```
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## Model description
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## Examples
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### How to load pre-trained model for Masked Language Modeling
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```python
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from transformers import AutoTokenizer, AutoModel
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tokenizer = AutoTokenizer.from_pretrained('AIRI-Institute/gena-lm-bigbird-base-sparse')
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model = AutoModel.from_pretrained('AIRI-Institute/gena-lm-bigbird-base-sparse', trust_remote_code=True)
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```
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### How to load pre-trained model to fine-tune it on classification task
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Get model class from GENA-LM repository:
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```bash
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git clone https://github.com/AIRI-Institute/GENA_LM.git
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```
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```python
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from GENA_LM.src.gena_lm.modeling_bert import BertForSequenceClassification
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from transformers import AutoTokenizer
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tokenizer = AutoTokenizer.from_pretrained('AIRI-Institute/gena-lm-bigbird-base-sparse')
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model = BertForSequenceClassification.from_pretrained('AIRI-Institute/gena-lm-bigbird-base-sparse')
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```
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or you can just download [modeling_bert.py](https://github.com/AIRI-Institute/GENA_LM/tree/main/src/gena_lm) and put it close to your code.
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OR you can get model class from HuggingFace AutoModel:
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```python
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from transformers import AutoTokenizer, AutoModel
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model = AutoModel.from_pretrained('AIRI-Institute/gena-lm-bigbird-base-sparse', trust_remote_code=True)
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gena_module_name = model.__class__.__module__
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print(gena_module_name)
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import importlib
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# available class names:
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# - BertModel, BertForPreTraining, BertForMaskedLM, BertForNextSentencePrediction,
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# - BertForSequenceClassification, BertForMultipleChoice, BertForTokenClassification,
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# - BertForQuestionAnswering
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# check https://huggingface.co/docs/transformers/model_doc/bert
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cls = getattr(importlib.import_module(gena_module_name), 'BertForSequenceClassification')
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print(cls)
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model = cls.from_pretrained('AIRI-Institute/gena-lm-bigbird-base-sparse', num_labels=2)
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```
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## Model description
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