What you need to do
```python
from transformers import AutoTokenizer, AutoModelForSequenceClassification

tokenizer = AutoTokenizer.from_pretrained("Jellywibble/12m-retry-continue-combined-regressor-epoch-1")
model = AutoModelForSequenceClassification.from_pretrained("Jellywibble/12m-retry-continue-combined-regressor-epoch-1")
tokenizer.pad_token_id = 50256
tokenizer.truncation_side = ‘left’
tokenizer.padding_side = ‘right’
tokens = self.eval_tokenizer(candidates, return_tensors='pt', return_attention_mask=True, padding='longest', truncation=True, max_length=256)
reward = model(**tokens).logits
```
{}
transformers pytorch gpt2 text-classification autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #gpt2 #text-classification #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

What you need to do

TAGS
#transformers #pytorch #gpt2 #text-classification #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

TAGS
#transformers #pytorch #gpt2 #text-classification #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
