Instructions to use huolongguo10/check_sec with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use huolongguo10/check_sec with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="huolongguo10/check_sec")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("huolongguo10/check_sec") model = AutoModelForSequenceClassification.from_pretrained("huolongguo10/check_sec", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
bb8978f
1
Parent(s): 0d7fc80
Upload BertForSequenceClassification (#3)
Browse files- Upload BertForSequenceClassification (6e229a29271fca23982d3314e361243fb2b180a1)
- config.json +2 -1
- pytorch_model.bin +1 -1
config.json
CHANGED
|
@@ -1,4 +1,5 @@
|
|
| 1 |
{
|
|
|
|
| 2 |
"architectures": [
|
| 3 |
"BertForSequenceClassification"
|
| 4 |
],
|
|
@@ -23,4 +24,4 @@
|
|
| 23 |
"type_vocab_size": 2,
|
| 24 |
"use_cache": true,
|
| 25 |
"vocab_size": 30522
|
| 26 |
-
}
|
|
|
|
| 1 |
{
|
| 2 |
+
"_name_or_path": "check_sec",
|
| 3 |
"architectures": [
|
| 4 |
"BertForSequenceClassification"
|
| 5 |
],
|
|
|
|
| 24 |
"type_vocab_size": 2,
|
| 25 |
"use_cache": true,
|
| 26 |
"vocab_size": 30522
|
| 27 |
+
}
|
pytorch_model.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 438007925
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:46b811bfe26e905399685834785d8189eb9de5d803a023c9ba79b8ea7ece3331
|
| 3 |
size 438007925
|