Text Classification
Transformers
ONNX
Safetensors
English
llama
reasoning-detection
small-model
tiny-model
english
34m
text-embeddings-inference
Instructions to use vrishv/thinker-34M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vrishv/thinker-34M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="vrishv/thinker-34M")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("vrishv/thinker-34M") model = AutoModelForSequenceClassification.from_pretrained("vrishv/thinker-34M", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 273 Bytes
cfe2d32 | 1 2 3 4 5 6 7 8 9 10 11 | {
"backend": "tokenizers",
"bos_token": "<|endoftext|>",
"eos_token": "<|endoftext|>",
"is_local": false,
"local_files_only": false,
"model_max_length": 1000000000000000019884624838656,
"pad_token": "<|endoftext|>",
"tokenizer_class": "TokenizersBackend"
}
|