Question Answering
Transformers
Safetensors
English
qwen2
text-generation
biology
medical
healthcare
text-generation-inference
Instructions to use HPAI-BSC/Qwen2.5-Aloe-Beta-7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HPAI-BSC/Qwen2.5-Aloe-Beta-7B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="HPAI-BSC/Qwen2.5-Aloe-Beta-7B")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("HPAI-BSC/Qwen2.5-Aloe-Beta-7B") model = AutoModelForCausalLM.from_pretrained("HPAI-BSC/Qwen2.5-Aloe-Beta-7B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 06d213500a65ce9c5910139d16bf99f9f466efe82aef9d618e43b675f91b203f
- Size of remote file:
- 4.93 GB
- SHA256:
- c5cbe5fd9715a476400eb4ca3a4b39729b075c23b0d90c829e330c4a0a617f4c
路
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