Add SetFit model
Browse files- 1_Pooling/config.json +7 -0
- README.md +214 -0
- config.json +24 -0
- config_sentence_transformers.json +7 -0
- config_setfit.json +4 -0
- model.safetensors +3 -0
- model_head.pkl +3 -0
- modules.json +14 -0
- sentence_bert_config.json +4 -0
- special_tokens_map.json +51 -0
- tokenizer.json +0 -0
- tokenizer_config.json +59 -0
- vocab.txt +0 -0
1_Pooling/config.json
ADDED
@@ -0,0 +1,7 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"word_embedding_dimension": 768,
|
3 |
+
"pooling_mode_cls_token": false,
|
4 |
+
"pooling_mode_mean_tokens": true,
|
5 |
+
"pooling_mode_max_tokens": false,
|
6 |
+
"pooling_mode_mean_sqrt_len_tokens": false
|
7 |
+
}
|
README.md
ADDED
@@ -0,0 +1,214 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
---
|
2 |
+
library_name: setfit
|
3 |
+
tags:
|
4 |
+
- setfit
|
5 |
+
- sentence-transformers
|
6 |
+
- text-classification
|
7 |
+
- generated_from_setfit_trainer
|
8 |
+
metrics:
|
9 |
+
- accuracy
|
10 |
+
widget:
|
11 |
+
- text: Buses are more simple - you just buy a ticket .
|
12 |
+
- text: As citizens of village , we totally care about environment of our village
|
13 |
+
.
|
14 |
+
- text: So , finally I suggest that it would be a great idea to combine the different
|
15 |
+
types of activities , both popular and the newest .
|
16 |
+
- text: Had 12 years old .
|
17 |
+
- text: On the other hand , I have the theoretical knowledge to use new the technologies
|
18 |
+
this great project requires .
|
19 |
+
pipeline_tag: text-classification
|
20 |
+
inference: true
|
21 |
+
base_model: sentence-transformers/paraphrase-mpnet-base-v2
|
22 |
+
model-index:
|
23 |
+
- name: SetFit with sentence-transformers/paraphrase-mpnet-base-v2
|
24 |
+
results:
|
25 |
+
- task:
|
26 |
+
type: text-classification
|
27 |
+
name: Text Classification
|
28 |
+
dataset:
|
29 |
+
name: Unknown
|
30 |
+
type: unknown
|
31 |
+
split: test
|
32 |
+
metrics:
|
33 |
+
- type: accuracy
|
34 |
+
value: 0.13152173913043477
|
35 |
+
name: Accuracy
|
36 |
+
---
|
37 |
+
|
38 |
+
# SetFit with sentence-transformers/paraphrase-mpnet-base-v2
|
39 |
+
|
40 |
+
This is a [SetFit](https://github.com/huggingface/setfit) model that can be used for Text Classification. This SetFit model uses [sentence-transformers/paraphrase-mpnet-base-v2](https://huggingface.co/sentence-transformers/paraphrase-mpnet-base-v2) as the Sentence Transformer embedding model. A [SetFitHead](huggingface.co/docs/setfit/reference/main#setfit.SetFitHead) instance is used for classification.
|
41 |
+
|
42 |
+
The model has been trained using an efficient few-shot learning technique that involves:
|
43 |
+
|
44 |
+
1. Fine-tuning a [Sentence Transformer](https://www.sbert.net) with contrastive learning.
|
45 |
+
2. Training a classification head with features from the fine-tuned Sentence Transformer.
|
46 |
+
|
47 |
+
## Model Details
|
48 |
+
|
49 |
+
### Model Description
|
50 |
+
- **Model Type:** SetFit
|
51 |
+
- **Sentence Transformer body:** [sentence-transformers/paraphrase-mpnet-base-v2](https://huggingface.co/sentence-transformers/paraphrase-mpnet-base-v2)
|
52 |
+
- **Classification head:** a [SetFitHead](huggingface.co/docs/setfit/reference/main#setfit.SetFitHead) instance
|
53 |
+
- **Maximum Sequence Length:** 512 tokens
|
54 |
+
- **Number of Classes:** 8 classes
|
55 |
+
<!-- - **Training Dataset:** [Unknown](https://huggingface.co/datasets/unknown) -->
|
56 |
+
<!-- - **Language:** Unknown -->
|
57 |
+
<!-- - **License:** Unknown -->
|
58 |
+
|
59 |
+
### Model Sources
|
60 |
+
|
61 |
+
- **Repository:** [SetFit on GitHub](https://github.com/huggingface/setfit)
|
62 |
+
- **Paper:** [Efficient Few-Shot Learning Without Prompts](https://arxiv.org/abs/2209.11055)
|
63 |
+
- **Blogpost:** [SetFit: Efficient Few-Shot Learning Without Prompts](https://huggingface.co/blog/setfit)
|
64 |
+
|
65 |
+
### Model Labels
|
66 |
+
| Label | Examples |
|
67 |
+
|:------|:----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
|
68 |
+
| 7 | <ul><li>"When I 've had a very bad and stressful day I can relax doing karate , because It 's the kind of sport that it is n't very hard ."</li><li>"Also , you 'll meet friendly people who usually ask to you something to be friends and change your telephone number ."</li><li>'When I have spare time , I often gather my friends to watch basketball match on television .'</li></ul> |
|
69 |
+
| 4 | <ul><li>"stop shouting . do n't shout ."</li><li>'Yours Sincerely .'</li><li>'Something that they don know was that the whole thing was a movie !'</li></ul> |
|
70 |
+
| 1 | <ul><li>'She stay sleeping in the bed and doing nothing all day .'</li><li>'People collects trash of their house and await the trash truck that carried the trash to a landfill located outside the village .'</li><li>"Travelling by car is n't so much more convenient unless it is so much more comfortable , but actually we do n't think about the contamination in our planet ."</li></ul> |
|
71 |
+
| 6 | <ul><li>'When the concert finished , we went to cloakroom to get signatures from musicians .'</li><li>'We have solar panels and a place to make compost at the last garden , with worms who eat and degrade all the organic waste of the school .'</li><li>'The aim of this report is to give you my personal point of view of the course I did in your branch in Madrid last month .'</li></ul> |
|
72 |
+
| 5 | <ul><li>'You can also bought a lot of gifts like key chains , statue , or what else memories to be made before returning to Malaysia .'</li><li>'I always said that I passed that test and I was sure of that .'</li><li>'In addition , to decrease the risk of negative comments or posts , Facebook and Twitter would improve their futures to solve the less personal privacy problem .'</li></ul> |
|
73 |
+
| 2 | <ul><li>'They were not only really clever people but also excellent co - workers .'</li><li>'On balance , learning foreign languages is very positive on different aspect , so if you have the positivity of learning a new language do it , because it will bring you many benefits .'</li><li>'In many years of work I have honed my skills in managing non - standard situations , analyzing the problem , finding and implementing practical and easy solutions .'</li></ul> |
|
74 |
+
| 0 | <ul><li>'It is very funny .'</li><li>'In China , English is took to be a foreign language which many students choose to learn .'</li><li>'We also value that they have specialised studies in Cloud technology , and hosting management .'</li></ul> |
|
75 |
+
| 3 | <ul><li>"Usually there are generation problems , sons do n't understand parents and vicecersa , but dialoging and listening emotions and facts , everyone can have another point of view ."</li><li>'the two boys heard that he was planing to steal some money and kill people so the boys start their adventure on stoping Injuin Joe ...'</li><li>'As an example , if you are able to get alone with your travel companion could enjoy each moment of the trip , exchange some pictures , eat together , and visit places with common interest such as museums or malls .'</li></ul> |
|
76 |
+
|
77 |
+
## Evaluation
|
78 |
+
|
79 |
+
### Metrics
|
80 |
+
| Label | Accuracy |
|
81 |
+
|:--------|:---------|
|
82 |
+
| **all** | 0.1315 |
|
83 |
+
|
84 |
+
## Uses
|
85 |
+
|
86 |
+
### Direct Use for Inference
|
87 |
+
|
88 |
+
First install the SetFit library:
|
89 |
+
|
90 |
+
```bash
|
91 |
+
pip install setfit
|
92 |
+
```
|
93 |
+
|
94 |
+
Then you can load this model and run inference.
|
95 |
+
|
96 |
+
```python
|
97 |
+
from setfit import SetFitModel
|
98 |
+
|
99 |
+
# Download from the 🤗 Hub
|
100 |
+
model = SetFitModel.from_pretrained("HelgeKn/BEA2019-multi-class-4")
|
101 |
+
# Run inference
|
102 |
+
preds = model("Had 12 years old .")
|
103 |
+
```
|
104 |
+
|
105 |
+
<!--
|
106 |
+
### Downstream Use
|
107 |
+
|
108 |
+
*List how someone could finetune this model on their own dataset.*
|
109 |
+
-->
|
110 |
+
|
111 |
+
<!--
|
112 |
+
### Out-of-Scope Use
|
113 |
+
|
114 |
+
*List how the model may foreseeably be misused and address what users ought not to do with the model.*
|
115 |
+
-->
|
116 |
+
|
117 |
+
<!--
|
118 |
+
## Bias, Risks and Limitations
|
119 |
+
|
120 |
+
*What are the known or foreseeable issues stemming from this model? You could also flag here known failure cases or weaknesses of the model.*
|
121 |
+
-->
|
122 |
+
|
123 |
+
<!--
|
124 |
+
### Recommendations
|
125 |
+
|
126 |
+
*What are recommendations with respect to the foreseeable issues? For example, filtering explicit content.*
|
127 |
+
-->
|
128 |
+
|
129 |
+
## Training Details
|
130 |
+
|
131 |
+
### Training Set Metrics
|
132 |
+
| Training set | Min | Median | Max |
|
133 |
+
|:-------------|:----|:--------|:----|
|
134 |
+
| Word count | 3 | 19.1562 | 42 |
|
135 |
+
|
136 |
+
| Label | Training Sample Count |
|
137 |
+
|:------|:----------------------|
|
138 |
+
| 0 | 4 |
|
139 |
+
| 1 | 4 |
|
140 |
+
| 2 | 4 |
|
141 |
+
| 3 | 4 |
|
142 |
+
| 4 | 4 |
|
143 |
+
| 5 | 4 |
|
144 |
+
| 6 | 4 |
|
145 |
+
| 7 | 4 |
|
146 |
+
|
147 |
+
### Training Hyperparameters
|
148 |
+
- batch_size: (16, 16)
|
149 |
+
- num_epochs: (2, 2)
|
150 |
+
- max_steps: -1
|
151 |
+
- sampling_strategy: oversampling
|
152 |
+
- num_iterations: 20
|
153 |
+
- body_learning_rate: (2e-05, 2e-05)
|
154 |
+
- head_learning_rate: 2e-05
|
155 |
+
- loss: CosineSimilarityLoss
|
156 |
+
- distance_metric: cosine_distance
|
157 |
+
- margin: 0.25
|
158 |
+
- end_to_end: False
|
159 |
+
- use_amp: False
|
160 |
+
- warmup_proportion: 0.1
|
161 |
+
- seed: 42
|
162 |
+
- eval_max_steps: -1
|
163 |
+
- load_best_model_at_end: False
|
164 |
+
|
165 |
+
### Training Results
|
166 |
+
| Epoch | Step | Training Loss | Validation Loss |
|
167 |
+
|:------:|:----:|:-------------:|:---------------:|
|
168 |
+
| 0.0125 | 1 | 0.1886 | - |
|
169 |
+
| 0.625 | 50 | 0.0778 | - |
|
170 |
+
| 1.25 | 100 | 0.0194 | - |
|
171 |
+
| 1.875 | 150 | 0.0069 | - |
|
172 |
+
|
173 |
+
### Framework Versions
|
174 |
+
- Python: 3.9.13
|
175 |
+
- SetFit: 1.0.1
|
176 |
+
- Sentence Transformers: 2.2.2
|
177 |
+
- Transformers: 4.36.0
|
178 |
+
- PyTorch: 2.1.1+cpu
|
179 |
+
- Datasets: 2.15.0
|
180 |
+
- Tokenizers: 0.15.0
|
181 |
+
|
182 |
+
## Citation
|
183 |
+
|
184 |
+
### BibTeX
|
185 |
+
```bibtex
|
186 |
+
@article{https://doi.org/10.48550/arxiv.2209.11055,
|
187 |
+
doi = {10.48550/ARXIV.2209.11055},
|
188 |
+
url = {https://arxiv.org/abs/2209.11055},
|
189 |
+
author = {Tunstall, Lewis and Reimers, Nils and Jo, Unso Eun Seo and Bates, Luke and Korat, Daniel and Wasserblat, Moshe and Pereg, Oren},
|
190 |
+
keywords = {Computation and Language (cs.CL), FOS: Computer and information sciences, FOS: Computer and information sciences},
|
191 |
+
title = {Efficient Few-Shot Learning Without Prompts},
|
192 |
+
publisher = {arXiv},
|
193 |
+
year = {2022},
|
194 |
+
copyright = {Creative Commons Attribution 4.0 International}
|
195 |
+
}
|
196 |
+
```
|
197 |
+
|
198 |
+
<!--
|
199 |
+
## Glossary
|
200 |
+
|
201 |
+
*Clearly define terms in order to be accessible across audiences.*
|
202 |
+
-->
|
203 |
+
|
204 |
+
<!--
|
205 |
+
## Model Card Authors
|
206 |
+
|
207 |
+
*Lists the people who create the model card, providing recognition and accountability for the detailed work that goes into its construction.*
|
208 |
+
-->
|
209 |
+
|
210 |
+
<!--
|
211 |
+
## Model Card Contact
|
212 |
+
|
213 |
+
*Provides a way for people who have updates to the Model Card, suggestions, or questions, to contact the Model Card authors.*
|
214 |
+
-->
|
config.json
ADDED
@@ -0,0 +1,24 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"_name_or_path": "C:\\Users\\Man_f/.cache\\torch\\sentence_transformers\\sentence-transformers_paraphrase-mpnet-base-v2\\",
|
3 |
+
"architectures": [
|
4 |
+
"MPNetModel"
|
5 |
+
],
|
6 |
+
"attention_probs_dropout_prob": 0.1,
|
7 |
+
"bos_token_id": 0,
|
8 |
+
"eos_token_id": 2,
|
9 |
+
"hidden_act": "gelu",
|
10 |
+
"hidden_dropout_prob": 0.1,
|
11 |
+
"hidden_size": 768,
|
12 |
+
"initializer_range": 0.02,
|
13 |
+
"intermediate_size": 3072,
|
14 |
+
"layer_norm_eps": 1e-05,
|
15 |
+
"max_position_embeddings": 514,
|
16 |
+
"model_type": "mpnet",
|
17 |
+
"num_attention_heads": 12,
|
18 |
+
"num_hidden_layers": 12,
|
19 |
+
"pad_token_id": 1,
|
20 |
+
"relative_attention_num_buckets": 32,
|
21 |
+
"torch_dtype": "float32",
|
22 |
+
"transformers_version": "4.36.0",
|
23 |
+
"vocab_size": 30527
|
24 |
+
}
|
config_sentence_transformers.json
ADDED
@@ -0,0 +1,7 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"__version__": {
|
3 |
+
"sentence_transformers": "2.0.0",
|
4 |
+
"transformers": "4.7.0",
|
5 |
+
"pytorch": "1.9.0+cu102"
|
6 |
+
}
|
7 |
+
}
|
config_setfit.json
ADDED
@@ -0,0 +1,4 @@
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"labels": null,
|
3 |
+
"normalize_embeddings": false
|
4 |
+
}
|
model.safetensors
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:7bba2812186f482f6848093fe2fc50cae5c0554b1d77ad023b8a1298602513f9
|
3 |
+
size 437967672
|
model_head.pkl
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:56eec723acfc91ef2ea01c5615a43f3d34a85d5a15627ac583ca5fbec40a4533
|
3 |
+
size 26128
|
modules.json
ADDED
@@ -0,0 +1,14 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
[
|
2 |
+
{
|
3 |
+
"idx": 0,
|
4 |
+
"name": "0",
|
5 |
+
"path": "",
|
6 |
+
"type": "sentence_transformers.models.Transformer"
|
7 |
+
},
|
8 |
+
{
|
9 |
+
"idx": 1,
|
10 |
+
"name": "1",
|
11 |
+
"path": "1_Pooling",
|
12 |
+
"type": "sentence_transformers.models.Pooling"
|
13 |
+
}
|
14 |
+
]
|
sentence_bert_config.json
ADDED
@@ -0,0 +1,4 @@
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"max_seq_length": 512,
|
3 |
+
"do_lower_case": false
|
4 |
+
}
|
special_tokens_map.json
ADDED
@@ -0,0 +1,51 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"bos_token": {
|
3 |
+
"content": "<s>",
|
4 |
+
"lstrip": false,
|
5 |
+
"normalized": false,
|
6 |
+
"rstrip": false,
|
7 |
+
"single_word": false
|
8 |
+
},
|
9 |
+
"cls_token": {
|
10 |
+
"content": "<s>",
|
11 |
+
"lstrip": false,
|
12 |
+
"normalized": true,
|
13 |
+
"rstrip": false,
|
14 |
+
"single_word": false
|
15 |
+
},
|
16 |
+
"eos_token": {
|
17 |
+
"content": "</s>",
|
18 |
+
"lstrip": false,
|
19 |
+
"normalized": false,
|
20 |
+
"rstrip": false,
|
21 |
+
"single_word": false
|
22 |
+
},
|
23 |
+
"mask_token": {
|
24 |
+
"content": "<mask>",
|
25 |
+
"lstrip": true,
|
26 |
+
"normalized": false,
|
27 |
+
"rstrip": false,
|
28 |
+
"single_word": false
|
29 |
+
},
|
30 |
+
"pad_token": {
|
31 |
+
"content": "<pad>",
|
32 |
+
"lstrip": false,
|
33 |
+
"normalized": false,
|
34 |
+
"rstrip": false,
|
35 |
+
"single_word": false
|
36 |
+
},
|
37 |
+
"sep_token": {
|
38 |
+
"content": "</s>",
|
39 |
+
"lstrip": false,
|
40 |
+
"normalized": true,
|
41 |
+
"rstrip": false,
|
42 |
+
"single_word": false
|
43 |
+
},
|
44 |
+
"unk_token": {
|
45 |
+
"content": "[UNK]",
|
46 |
+
"lstrip": false,
|
47 |
+
"normalized": false,
|
48 |
+
"rstrip": false,
|
49 |
+
"single_word": false
|
50 |
+
}
|
51 |
+
}
|
tokenizer.json
ADDED
The diff for this file is too large to render.
See raw diff
|
|
tokenizer_config.json
ADDED
@@ -0,0 +1,59 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"added_tokens_decoder": {
|
3 |
+
"0": {
|
4 |
+
"content": "<s>",
|
5 |
+
"lstrip": false,
|
6 |
+
"normalized": false,
|
7 |
+
"rstrip": false,
|
8 |
+
"single_word": false,
|
9 |
+
"special": true
|
10 |
+
},
|
11 |
+
"1": {
|
12 |
+
"content": "<pad>",
|
13 |
+
"lstrip": false,
|
14 |
+
"normalized": false,
|
15 |
+
"rstrip": false,
|
16 |
+
"single_word": false,
|
17 |
+
"special": true
|
18 |
+
},
|
19 |
+
"2": {
|
20 |
+
"content": "</s>",
|
21 |
+
"lstrip": false,
|
22 |
+
"normalized": false,
|
23 |
+
"rstrip": false,
|
24 |
+
"single_word": false,
|
25 |
+
"special": true
|
26 |
+
},
|
27 |
+
"104": {
|
28 |
+
"content": "[UNK]",
|
29 |
+
"lstrip": false,
|
30 |
+
"normalized": false,
|
31 |
+
"rstrip": false,
|
32 |
+
"single_word": false,
|
33 |
+
"special": true
|
34 |
+
},
|
35 |
+
"30526": {
|
36 |
+
"content": "<mask>",
|
37 |
+
"lstrip": true,
|
38 |
+
"normalized": false,
|
39 |
+
"rstrip": false,
|
40 |
+
"single_word": false,
|
41 |
+
"special": true
|
42 |
+
}
|
43 |
+
},
|
44 |
+
"bos_token": "<s>",
|
45 |
+
"clean_up_tokenization_spaces": true,
|
46 |
+
"cls_token": "<s>",
|
47 |
+
"do_basic_tokenize": true,
|
48 |
+
"do_lower_case": true,
|
49 |
+
"eos_token": "</s>",
|
50 |
+
"mask_token": "<mask>",
|
51 |
+
"model_max_length": 512,
|
52 |
+
"never_split": null,
|
53 |
+
"pad_token": "<pad>",
|
54 |
+
"sep_token": "</s>",
|
55 |
+
"strip_accents": null,
|
56 |
+
"tokenize_chinese_chars": true,
|
57 |
+
"tokenizer_class": "MPNetTokenizer",
|
58 |
+
"unk_token": "[UNK]"
|
59 |
+
}
|
vocab.txt
ADDED
The diff for this file is too large to render.
See raw diff
|
|