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:
- acf6feab81a7a3126f3a578ce9b228664b432f8f411276bf240b729f4bf5aceb
- Size of remote file:
- 1.17 GB
- SHA256:
- 6a556a2ca1f728cdc009fb2810fc6bd2ee9843e154c164a7a5396a1865d510db
路
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