JYYong nazneen commited on
Commit
a9e0708
1 Parent(s): 74f0679

model documentation (#1)

Browse files

- model documentation (3ba7c31ebdacc40fcdb155cd55c5baaaea5fc0a4)


Co-authored-by: Nazneen Rajani <nazneen@users.noreply.huggingface.co>

Files changed (1) hide show
  1. README.md +177 -0
README.md ADDED
@@ -0,0 +1,177 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ tags:
3
+ - fill-mask
4
+ - deberta
5
+ ---
6
+
7
+ # Model Card for patentdeberta_base_spec_1024_pwi
8
+
9
+ # Model Details
10
+
11
+ ## Model Description
12
+
13
+ More information needed
14
+
15
+ - **Developed by:** More information needed
16
+ - **Shared by [Optional]:** tanapatentlm
17
+ - **Model type:** Fill Mask
18
+ - **Language(s) (NLP):** More information needed
19
+ - **License:** More information needed
20
+ - **Parent Model:** [DeBERTa](https://huggingface.co/microsoft/deberta-base?text=The+goal+of+life+is+%5BMASK%5D.)
21
+ - **Resources for more information:** More information needed
22
+
23
+
24
+ # Uses
25
+
26
+
27
+ ## Direct Use
28
+ This model can be used for the task of Fill Mask.
29
+
30
+ ## Downstream Use [Optional]
31
+
32
+ More information needed.
33
+
34
+ ## Out-of-Scope Use
35
+
36
+ The model should not be used to intentionally create hostile or alienating environments for people.
37
+
38
+ # Bias, Risks, and Limitations
39
+
40
+
41
+ Significant research has explored bias and fairness issues with language models (see, e.g., [Sheng et al. (2021)](https://aclanthology.org/2021.acl-long.330.pdf) and [Bender et al. (2021)](https://dl.acm.org/doi/pdf/10.1145/3442188.3445922)). Predictions generated by the model may include disturbing and harmful stereotypes across protected classes; identity characteristics; and sensitive, social, and occupational groups.
42
+
43
+
44
+
45
+ ## Recommendations
46
+
47
+
48
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
49
+
50
+ # Training Details
51
+
52
+ ## Training Data
53
+
54
+ More information needed
55
+
56
+ ## Training Procedure
57
+
58
+
59
+ ### Preprocessing
60
+
61
+ More information needed
62
+
63
+
64
+
65
+ ### Speeds, Sizes, Times
66
+
67
+ More information needed
68
+
69
+
70
+
71
+ # Evaluation
72
+
73
+
74
+ ## Testing Data, Factors & Metrics
75
+
76
+ ### Testing Data
77
+
78
+ More information needed
79
+
80
+ ### Factors
81
+ More information needed
82
+
83
+ ### Metrics
84
+
85
+ More information needed
86
+
87
+
88
+ ## Results
89
+
90
+ More information needed
91
+
92
+
93
+ # Model Examination
94
+
95
+ More information needed
96
+
97
+ # Environmental Impact
98
+
99
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
100
+
101
+ - **Hardware Type:** More information needed
102
+ - **Hours used:** More information needed
103
+ - **Cloud Provider:** More information needed
104
+ - **Compute Region:** More information needed
105
+ - **Carbon Emitted:** More information needed
106
+
107
+ # Technical Specifications [optional]
108
+
109
+ ## Model Architecture and Objective
110
+
111
+ More information needed
112
+
113
+ ## Compute Infrastructure
114
+
115
+ More information needed
116
+
117
+ ### Hardware
118
+
119
+
120
+ More information needed
121
+
122
+ ### Software
123
+
124
+ More information needed.
125
+
126
+ # Citation
127
+
128
+
129
+ **BibTeX:**
130
+
131
+ More information needed
132
+ ```bibtex
133
+ @inproceedings{
134
+ he2021deberta,
135
+ title={DEBERTA: DECODING-ENHANCED BERT WITH DISENTANGLED ATTENTION},
136
+ author={Pengcheng He and Xiaodong Liu and Jianfeng Gao and Weizhu Chen},
137
+ booktitle={International Conference on Learning Representations},
138
+ year={2021},
139
+ url={https://openreview.net/forum?id=XPZIaotutsD}
140
+ }
141
+ ```
142
+
143
+
144
+ **APA:**
145
+
146
+ More information needed
147
+
148
+ # Glossary [optional]
149
+
150
+ More information needed
151
+
152
+ # More Information [optional]
153
+ More information needed
154
+
155
+ # Model Card Authors [optional]
156
+
157
+ Tanapatentlm in collaboration with Ezi Ozoani and the Hugging Face team
158
+
159
+ # Model Card Contact
160
+
161
+ More information needed
162
+
163
+ # How to Get Started with the Model
164
+
165
+ Use the code below to get started with the model.
166
+
167
+ <details>
168
+ <summary> Click to expand </summary>
169
+
170
+ ```python
171
+ from transformers import AutoTokenizer, AutoModelForMaskedLM
172
+
173
+ tokenizer = AutoTokenizer.from_pretrained("tanapatentlm/patentdeberta_base_spec_1024_pwi")
174
+
175
+ model = AutoModelForMaskedLM.from_pretrained("tanapatentlm/patentdeberta_base_spec_1024_pwi")
176
+ ```
177
+ </details>