Instructions to use Jose-Ribeir/stt_Huggin_face_tech_new_data with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jose-Ribeir/stt_Huggin_face_tech_new_data with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "question-answering" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("question-answering", model="Jose-Ribeir/stt_Huggin_face_tech_new_data")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("Jose-Ribeir/stt_Huggin_face_tech_new_data") model = AutoModelForQuestionAnswering.from_pretrained("Jose-Ribeir/stt_Huggin_face_tech_new_data", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 1
Browse files- model.safetensors +1 -1
- training_args.bin +1 -1
model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 265470032
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:4a47853d2d39eefa9060df0e6f85c4fc6f548bc94e93f19c09ed3c24460728e7
|
| 3 |
size 265470032
|
training_args.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 4984
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:27352332a37c27bac43a0f88aef0142f965cbbc63b166d9eb309059e81fab106
|
| 3 |
size 4984
|