Text Classification
Transformers
Safetensors
English
bert
text-generation-inference
unsloth
trl
text-embeddings-inference
Instructions to use dataak-ai/dk-sentiment-tookabert-base-unsloth with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dataak-ai/dk-sentiment-tookabert-base-unsloth with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dataak-ai/dk-sentiment-tookabert-base-unsloth")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dataak-ai/dk-sentiment-tookabert-base-unsloth") model = AutoModelForSequenceClassification.from_pretrained("dataak-ai/dk-sentiment-tookabert-base-unsloth", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Uploaded model
- Developed by: dataak-ai
- License: apache-2.0
- Finetuned from model : PartAI/TookaBERT-Base
This bert model was trained 2x faster with Unsloth and Huggingface's TRL library.
- Downloads last month
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Model tree for dataak-ai/dk-sentiment-tookabert-base-unsloth
Base model
PartAI/TookaBERT-Base