Instructions to use l3cube-pune/marathi-mixed-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use l3cube-pune/marathi-mixed-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="l3cube-pune/marathi-mixed-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("l3cube-pune/marathi-mixed-ner") model = AutoModelForTokenClassification.from_pretrained("l3cube-pune/marathi-mixed-ner", 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:ad07b13f2c1fe0c461e9135c15e1110b4365a84683d5adf02b5607521622b141
|
| 3 |
+
size 947914680
|