Question Answering
Transformers
PyTorch
Safetensors
English
llama
text-generation
biology
medical
text-generation-inference
Instructions to use HPAI-BSC/Llama3-Aloe-8B-Alpha with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HPAI-BSC/Llama3-Aloe-8B-Alpha with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="HPAI-BSC/Llama3-Aloe-8B-Alpha")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("HPAI-BSC/Llama3-Aloe-8B-Alpha") model = AutoModelForCausalLM.from_pretrained("HPAI-BSC/Llama3-Aloe-8B-Alpha") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c17943918f75b91d6262f58d623067ba7563fac0708929e85d562de2fa6377de
- Size of remote file:
- 4.98 GB
- SHA256:
- 3b90d0b6a5e840e2f4bc9106407591eb2a881d1c69de3dd8b6dfac78f73a4adf
路
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