Feature Extraction
Transformers
PyTorch
Safetensors
Fairseq
French
pantagruel_uni
data2vec2
JEPA
text
custom_code
Instructions to use PantagrueLLM/text-base-wiki with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PantagrueLLM/text-base-wiki with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="PantagrueLLM/text-base-wiki", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("PantagrueLLM/text-base-wiki", trust_remote_code=True, device_map="auto") - Fairseq
How to use PantagrueLLM/text-base-wiki with Fairseq:
from fairseq.checkpoint_utils import load_model_ensemble_and_task_from_hf_hub models, cfg, task = load_model_ensemble_and_task_from_hf_hub( "PantagrueLLM/text-base-wiki" ) - Notebooks
- Google Colab
- Kaggle
Upload folder using huggingface_hub
Browse files- model.safetensors +3 -0
model.safetensors
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