Text Classification
Transformers
Safetensors
English
llama
moderation
toxicity
content-moderation
safety
quark
multi-label-classification
jigsaw
hate-speech
italian-ai
text-embeddings-inference
Instructions to use ThingAI/Quark-Mod with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ThingAI/Quark-Mod with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ThingAI/Quark-Mod")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ThingAI/Quark-Mod") model = AutoModelForSequenceClassification.from_pretrained("ThingAI/Quark-Mod") - Notebooks
- Google Colab
- Kaggle
| {% for message in messages %}{% if message['role'] == 'system' %}<|system|> | |
| {{ message['content'] }} | |
| {% elif message['role'] == 'user' %}<|user|> | |
| {{ message['content'] }} | |
| {% elif message['role'] == 'assistant' %}<|assistant|> | |
| {{ message['content'] }}{% if not loop.last %} | |
| {% endif %}{% endif %}{% endfor %}{% if messages[-1]['role'] != 'assistant' %}<|assistant|> | |
| {% endif %} |