Migrate model card from transformers-repo
Browse filesRead announcement at https://discuss.huggingface.co/t/announcement-all-model-cards-will-be-migrated-to-hf-co-model-repos/2755
Original file history: https://github.com/huggingface/transformers/commits/master/model_cards/gaochangkuan/model_dir/README.md
README.md
ADDED
@@ -0,0 +1,66 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
## Generating Chinese poetry by topic.
|
2 |
+
|
3 |
+
```python
|
4 |
+
from transformers import *
|
5 |
+
|
6 |
+
tokenizer = BertTokenizer.from_pretrained("gaochangkuan/model_dir")
|
7 |
+
|
8 |
+
model = AutoModelWithLMHead.from_pretrained("gaochangkuan/model_dir")
|
9 |
+
|
10 |
+
|
11 |
+
prompt= '''<s>田园躬耕'''
|
12 |
+
|
13 |
+
length= 84
|
14 |
+
stop_token='</s>'
|
15 |
+
|
16 |
+
temperature = 1.2
|
17 |
+
|
18 |
+
repetition_penalty=1.3
|
19 |
+
|
20 |
+
k= 30
|
21 |
+
p= 0.95
|
22 |
+
|
23 |
+
device ='cuda'
|
24 |
+
seed=2020
|
25 |
+
no_cuda=False
|
26 |
+
|
27 |
+
prompt_text = prompt if prompt else input("Model prompt >>> ")
|
28 |
+
|
29 |
+
encoded_prompt = tokenizer.encode(
|
30 |
+
'<s>'+prompt_text+'<sep>',
|
31 |
+
add_special_tokens=False,
|
32 |
+
return_tensors="pt"
|
33 |
+
)
|
34 |
+
|
35 |
+
encoded_prompt = encoded_prompt.to(device)
|
36 |
+
|
37 |
+
output_sequences = model.generate(
|
38 |
+
input_ids=encoded_prompt,
|
39 |
+
max_length=length,
|
40 |
+
min_length=10,
|
41 |
+
do_sample=True,
|
42 |
+
early_stopping=True,
|
43 |
+
num_beams=10,
|
44 |
+
temperature=temperature,
|
45 |
+
top_k=k,
|
46 |
+
top_p=p,
|
47 |
+
repetition_penalty=repetition_penalty,
|
48 |
+
bad_words_ids=None,
|
49 |
+
bos_token_id=tokenizer.bos_token_id,
|
50 |
+
pad_token_id=tokenizer.pad_token_id,
|
51 |
+
eos_token_id=tokenizer.eos_token_id,
|
52 |
+
length_penalty=1.2,
|
53 |
+
no_repeat_ngram_size=2,
|
54 |
+
num_return_sequences=1,
|
55 |
+
attention_mask=None,
|
56 |
+
decoder_start_token_id=tokenizer.bos_token_id,)
|
57 |
+
|
58 |
+
|
59 |
+
generated_sequence = output_sequences[0].tolist()
|
60 |
+
text = tokenizer.decode(generated_sequence)
|
61 |
+
|
62 |
+
|
63 |
+
text = text[: text.find(stop_token) if stop_token else None]
|
64 |
+
|
65 |
+
print(''.join(text).replace(' ','').replace('<pad>','').replace('<s>',''))
|
66 |
+
```
|