Text Classification
Transformers
PyTorch
TensorFlow
Safetensors
English
t5
text2text-generation
token-classification
question-answering
text-generation
Instructions to use razent/SciFive-base-PMC with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use razent/SciFive-base-PMC with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="razent/SciFive-base-PMC")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("razent/SciFive-base-PMC") model = AutoModelForSeq2SeqLM.from_pretrained("razent/SciFive-base-PMC") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#2
by SFconvertbot - opened
- .gitattributes +1 -0
- model.safetensors +3 -0
.gitattributes
CHANGED
|
@@ -14,3 +14,4 @@
|
|
| 14 |
*.pb filter=lfs diff=lfs merge=lfs -text
|
| 15 |
*.pt filter=lfs diff=lfs merge=lfs -text
|
| 16 |
*.pth filter=lfs diff=lfs merge=lfs -text
|
|
|
|
|
|
| 14 |
*.pb filter=lfs diff=lfs merge=lfs -text
|
| 15 |
*.pt filter=lfs diff=lfs merge=lfs -text
|
| 16 |
*.pth filter=lfs diff=lfs merge=lfs -text
|
| 17 |
+
model.safetensors filter=lfs diff=lfs merge=lfs -text
|
model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:7fa64ab019168880cfcec0f44f3e5d872041e9327a890d5cd047eeff7663b4e4
|
| 3 |
+
size 891644712
|