This model is funetune version of Codebert in roberta. On CodeSearchNet.
###
Quick start:

from transformers import AutoTokenizer, AutoModelForSequenceClassification

tokenizer = AutoTokenizer.from_pretrained("addy88/programming-lang-identifier")

model = AutoModelForSequenceClassification.from_pretrained("addy88/programming-lang-identifier")

input_ids = tokenizer.encode(CODE_TO_IDENTIFY)
logits = model(input_ids)[0]

language_idx = logits.argmax() # index for the resulting label
###
{}
transformers pytorch roberta text-classification autotrain_compatible endpoints_compatible has_space region:us
TAGS
#transformers #pytorch #roberta #text-classification #autotrain_compatible #endpoints_compatible #has_space #region-us 

This model is funetune version of Codebert in roberta. On CodeSearchNet.
###
Quick start:

from transformers import AutoTokenizer, AutoModelForSequenceClassification

tokenizer = AutoTokenizer.from_pretrained("addy88/programming-lang-identifier")

model = AutoModelForSequenceClassification.from_pretrained("addy88/programming-lang-identifier")

input_ids = URL(CODE_TO_IDENTIFY)
logits = model(input_ids)[0]

language_idx = URL() # index for the resulting label
###
# index for the resulting label
TAGS
#transformers #pytorch #roberta #text-classification #autotrain_compatible #endpoints_compatible #has_space #region-us 
 # index for the resulting label
passage: TAGS
#transformers #pytorch #roberta #text-classification #autotrain_compatible #endpoints_compatible #has_space #region-us 
# index for the resulting label