Instructions to use cp500/mlm-heb-medical with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cp500/mlm-heb-medical with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="cp500/mlm-heb-medical")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("cp500/mlm-heb-medical") model = AutoModelForMaskedLM.from_pretrained("cp500/mlm-heb-medical", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 500
Browse files- pytorch_model.bin +1 -1
- training_args.bin +1 -1
pytorch_model.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 737968565
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:91bc3aac87925fa78152ed4eed4d33f313e1d28d617158f36aa01c1d7fd2c079
|
| 3 |
size 737968565
|
training_args.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 4091
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:ec5c97347faf473ead0033bd1865e703b07f2becc505f6158f3a67b28ff0caa3
|
| 3 |
size 4091
|