Text Classification
Transformers
Safetensors
PEFT
qwen3
sequence-classification
decision-scoring
fura
vllm
text-embeddings-inference
Instructions to use whadupapp/goff-lite with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use whadupapp/goff-lite with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="whadupapp/goff-lite")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("whadupapp/goff-lite") model = AutoModelForSequenceClassification.from_pretrained("whadupapp/goff-lite", device_map="auto") - PEFT
How to use whadupapp/goff-lite with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from whadupapp/goff-lite: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/whadupapp/goff-lite/resolve/main/tokenizer.json
- Command line
-
hf download hf://whadupapp/goff-lite/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/whadupapp/goff-lite/resolve/main/tokenizer.json
11.4 MB
- Xet hash:
- d62484fd75fd6c2ece9e689988ae1f0ae0d7b198bb38b4f57c21d47d9801fd69
- Size of remote file:
- 11.4 MB
- SHA256:
- 642b05b6b6732f9ef1189d89d58c713112ac377bc857b9633423ced970a111ae
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