Summarization
Transformers
PyTorch
TensorFlow
Safetensors
English
bart
text2text-generation
seq2seq
Eval Results (legacy)
Instructions to use knkarthick/MEETING_SUMMARY with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use knkarthick/MEETING_SUMMARY with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "summarization" 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("summarization", model="knkarthick/MEETING_SUMMARY")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("knkarthick/MEETING_SUMMARY") model = AutoModelForSeq2SeqLM.from_pretrained("knkarthick/MEETING_SUMMARY", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Commit ·
73d3333
1
Parent(s): c24e305
Add TF weights (#1)
Browse files- Add TF weights (ae41c6e3c74153345e0da00775b0c6a5b359e00a)
Co-authored-by: Joao Gante <joaogante@users.noreply.huggingface.co>
- tf_model.h5 +3 -0
tf_model.h5
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:6158cc106a06639f1aee5e073bff0b8d8e42361da1ce4bb6a164b16ed07586ff
|
| 3 |
+
size 1625921384
|