Instructions to use Hartunka/bert_base_rand_10_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Hartunka/bert_base_rand_10_v2 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, DistilBertForLDAMaskedLM tokenizer = AutoTokenizer.from_pretrained("Hartunka/bert_base_rand_10_v2") model = DistilBertForLDAMaskedLM.from_pretrained("Hartunka/bert_base_rand_10_v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 20000
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 440468976
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:81bf60e4d6e7d67d3abadff8d4289585567ba0a986848d432f3f28974b1b0e6b
|
| 3 |
size 440468976
|