Instructions to use YakovElm/Apache_5_GPT2_Microsoft_Under_Sampling with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use YakovElm/Apache_5_GPT2_Microsoft_Under_Sampling with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="YakovElm/Apache_5_GPT2_Microsoft_Under_Sampling")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("YakovElm/Apache_5_GPT2_Microsoft_Under_Sampling") model = AutoModelForSequenceClassification.from_pretrained("YakovElm/Apache_5_GPT2_Microsoft_Under_Sampling") - Notebooks
- Google Colab
- Kaggle
Commit ·
fd4ce20
1
Parent(s): 8be8886
Adding `safetensors` variant of this model
Browse filesThis is an automated PR created with https://huggingface.co/spaces/safetensors/convert
This new file is equivalent to `pytorch_model.bin` but safe in the sense that
no arbitrary code can be put into it.
These files also happen to load much faster than their pytorch counterpart:
https://colab.research.google.com/github/huggingface/notebooks/blob/main/safetensors_doc/en/speed.ipynb
The widgets on your model page will run using this model even if this is not merged
making sure the file actually works.
If you find any issues: please report here: https://huggingface.co/spaces/safetensors/convert/discussions
Feel free to ignore this PR.
- model.safetensors +3 -0
model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:a323186d0c5729f196deaa98b46bdbf3aaa6bee56cc9dbe284a6e95275499f30
|
| 3 |
+
size 1444497968
|