Question Answering
Transformers
Safetensors
Swahili
English
llama
text-generation
text-generation-inference
Instructions to use Jacaranda/UlizaLlama3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jacaranda/UlizaLlama3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="Jacaranda/UlizaLlama3")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Jacaranda/UlizaLlama3") model = AutoModelForCausalLM.from_pretrained("Jacaranda/UlizaLlama3") - Notebooks
- Google Colab
- Kaggle
Creating gguf for UlizaLlama3
#1
by MeHereDude - opened
No description provided.
MeHereDude changed pull request status to open
Add UlizaLlama3 model in GGUF format
- Model: UlizaLlama3
- Format: GGUF (GPTQ-for-GGML Unified Format)
- Includes tokenizer and configuration files
- Optimized for memory-efficient inference
- Tested compatibility with popular GGUF frameworks
- Updated documentation for GGUF usage
- Added performance benchmarks and model specs
Closes #pr/1:refs/pr/1
MeHereDude changed pull request status to closed