Question Answering
Transformers
Safetensors
rag
retrieval-augmented-generation
multilingual
faiss
llama
mistral
Instructions to use hamzi275/multilingual with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hamzi275/multilingual with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="hamzi275/multilingual")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("hamzi275/multilingual", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| [ | |
| { | |
| "idx": 0, | |
| "name": "0", | |
| "path": "", | |
| "type": "sentence_transformers.models.Transformer" | |
| }, | |
| { | |
| "idx": 1, | |
| "name": "1", | |
| "path": "1_Pooling", | |
| "type": "sentence_transformers.models.Pooling" | |
| } | |
| ] |