nielsr HF staff kamalkraj commited on
Commit
ef3fc6f
1 Parent(s): 73440ec

Update README.md (#3)

Browse files

- Update README.md (248b4eb430f3f90fa6ed37048ad75b50d774e1ee)


Co-authored-by: Kamal Raj Kanakarajan <[email protected]>

Files changed (1) hide show
  1. README.md +9 -9
README.md CHANGED
@@ -12,9 +12,9 @@ set a seed for reproducibility:
12
 
13
  ```python
14
  >>> from transformers import pipeline, set_seed
15
- >>> from transformers import BioGptTokenizer, BioGptLMHeadModel
16
- >>> model = BioGptLMHeadModel.from_pretrained("kamalkraj/biogpt")
17
- >>> tokenizer = BioGptTokenizer.from_pretrained("kamalkraj/biogpt")
18
  >>> generator = pipeline('text-generation', model=model, tokenizer=tokenizer)
19
  >>> set_seed(42)
20
  >>> generator("COVID-19 is", max_length=20, num_return_sequences=5, do_sample=True)
@@ -28,9 +28,9 @@ set a seed for reproducibility:
28
  Here is how to use this model to get the features of a given text in PyTorch:
29
 
30
  ```python
31
- from transformers import BioGptTokenizer, BioGptModel
32
- tokenizer = BioGptTokenizer.from_pretrained("kamalkraj/biogpt")
33
- model = BioGptModel.from_pretrained("kamalkraj/biogpt")
34
  text = "Replace me by any text you'd like."
35
  encoded_input = tokenizer(text, return_tensors='pt')
36
  output = model(**encoded_input)
@@ -40,10 +40,10 @@ Beam-search decoding:
40
 
41
  ```python
42
  import torch
43
- from transformers import BioGptTokenizer, BioGptLMHeadModel, set_seed
44
 
45
- tokenizer = BioGptTokenizer.from_pretrained("kamalkraj/biogpt")
46
- model = BioGptLMHeadModel.from_pretrained("kamalkraj/biogpt")
47
 
48
  sentence = "COVID-19 is"
49
  inputs = tokenizer(sentence, return_tensors="pt")
 
12
 
13
  ```python
14
  >>> from transformers import pipeline, set_seed
15
+ >>> from transformers import BioGptTokenizer, BioGptForCausalLM
16
+ >>> model = BioGptForCausalLM.from_pretrained("microsoft/biogpt")
17
+ >>> tokenizer = BioGptTokenizer.from_pretrained("microsoft/biogpt")
18
  >>> generator = pipeline('text-generation', model=model, tokenizer=tokenizer)
19
  >>> set_seed(42)
20
  >>> generator("COVID-19 is", max_length=20, num_return_sequences=5, do_sample=True)
 
28
  Here is how to use this model to get the features of a given text in PyTorch:
29
 
30
  ```python
31
+ from transformers import BioGptTokenizer, BioGptForCausalLM
32
+ tokenizer = BioGptTokenizer.from_pretrained("microsoft/biogpt")
33
+ model = BioGptForCausalLM.from_pretrained("microsoft/biogpt")
34
  text = "Replace me by any text you'd like."
35
  encoded_input = tokenizer(text, return_tensors='pt')
36
  output = model(**encoded_input)
 
40
 
41
  ```python
42
  import torch
43
+ from transformers import BioGptTokenizer, BioGptForCausalLM, set_seed
44
 
45
+ tokenizer = BioGptTokenizer.from_pretrained("microsoft/biogpt")
46
+ model = BioGptForCausalLM.from_pretrained("microsoft/biogpt")
47
 
48
  sentence = "COVID-19 is"
49
  inputs = tokenizer(sentence, return_tensors="pt")