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
| { | |
| "add_prefix_space": false, | |
| "backend": "tokenizers", | |
| "bos_token": "<|endoftext|>", | |
| "clean_up_tokenization_spaces": false, | |
| "eos_token": "<|endoftext|>", | |
| "errors": "replace", | |
| "extra_special_tokens": [ | |
| "<|endoftext|>", | |
| "<|im_start|>", | |
| "<|im_end|>", | |
| "<repo_name>", | |
| "<reponame>", | |
| "<file_sep>", | |
| "<filename>", | |
| "<gh_stars>", | |
| "<issue_start>", | |
| "<issue_comment>", | |
| "<issue_closed>", | |
| "<jupyter_start>", | |
| "<jupyter_text>", | |
| "<jupyter_code>", | |
| "<jupyter_output>", | |
| "<jupyter_script>", | |
| "<empty_output>" | |
| ], | |
| "is_local": false, | |
| "local_files_only": false, | |
| "model_max_length": 1000000000000000019884624838656, | |
| "pad_token": "<|endoftext|>", | |
| "tokenizer_class": "GPT2Tokenizer", | |
| "unk_token": "<|endoftext|>", | |
| "vocab_size": 49152 | |
| } | |