Create README.md
Browse files
README.md
ADDED
@@ -0,0 +1,23 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
SQuAD 1.1 question-answering based on T5-small.
|
2 |
+
Example use:
|
3 |
+
|
4 |
+
```python
|
5 |
+
from transformers import T5Config, T5ForConditionalGeneration, T5Tokenizer
|
6 |
+
|
7 |
+
model_name = "allenai/t5-small-next-word-generator-qoogle"
|
8 |
+
tokenizer = T5Tokenizer.from_pretrained(model_name)
|
9 |
+
model = T5ForConditionalGeneration.from_pretrained(model_name)
|
10 |
+
|
11 |
+
def run_model(input_string, **generator_args):
|
12 |
+
input_ids = tokenizer.encode(input_string, return_tensors="pt")
|
13 |
+
res = model.generate(input_ids, **generator_args)
|
14 |
+
output = tokenizer.batch_decode(res, skip_special_tokens=True)
|
15 |
+
print(output)
|
16 |
+
return output
|
17 |
+
|
18 |
+
run_model("Who is the winner of 2009 olympics? \n Jack and Jill participated, but James won the games.")```
|
19 |
+
which should result in the following:
|
20 |
+
```
|
21 |
+
['James']
|
22 |
+
```
|
23 |
+
|