Question Answering
Transformers
PyTorch
Swahili
English
llama
text-generation
text-generation-inference
Instructions to use Jacaranda/UlizaLlama with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jacaranda/UlizaLlama with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "question-answering" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("question-answering", model="Jacaranda/UlizaLlama")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Jacaranda/UlizaLlama") model = AutoModelForCausalLM.from_pretrained("Jacaranda/UlizaLlama", device_map="auto") - Notebooks
- Google Colab
- Kaggle
TemporalMesh Transformer: 29.4 PPL at 48% compute — beats Mamba, new open-source architecture
#4 opened 4 months ago
by
vigneshwar234
Adding `safetensors` variant of this model
#3 opened almost 2 years ago
by
SFconvertbot
Update README.md
1
#2 opened over 2 years ago
by
Mollel
Request: DOI
#1 opened almost 3 years ago
by
poppingtonic