Instructions to use obss/roberta-large-answer-extraction-mrqa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use obss/roberta-large-answer-extraction-mrqa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="obss/roberta-large-answer-extraction-mrqa")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("obss/roberta-large-answer-extraction-mrqa") model = AutoModelForTokenClassification.from_pretrained("obss/roberta-large-answer-extraction-mrqa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:a399a6d09b20326aa2016cfce42249c295ba700f0fe6ddd8e0b21d9ab15c14e4
|
| 3 |
+
size 1417309196
|