Text Classification
Transformers
TensorBoard
Safetensors
English
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use Hartunka/bert_base_rand_5_v2_sst2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Hartunka/bert_base_rand_5_v2_sst2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Hartunka/bert_base_rand_5_v2_sst2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Hartunka/bert_base_rand_5_v2_sst2") model = AutoModelForSequenceClassification.from_pretrained("Hartunka/bert_base_rand_5_v2_sst2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 129 Bytes
ff38084 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:c094696d88e9136d9f62e947788991423dd654719032c862c928a765d76b12db
size 5368
|