Instructions to use dtorber/BioNLP-tech-decoder-PLOS with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dtorber/BioNLP-tech-decoder-PLOS with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "summarization" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("summarization", model="dtorber/BioNLP-tech-decoder-PLOS")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("dtorber/BioNLP-tech-decoder-PLOS") model = AutoModelForSeq2SeqLM.from_pretrained("dtorber/BioNLP-tech-decoder-PLOS") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 4
Browse files- model.safetensors +1 -1
model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 647641800
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:a816513f3e92ccbab33f4fd969c4ced34d7f05df720454cd6852229d74bf0e55
|
| 3 |
size 647641800
|