Question Answering
Transformers
Safetensors
Chinese
English
llama
text-generation
custom_code
text-generation-inference
Instructions to use FlagAlpha/Atom-7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FlagAlpha/Atom-7B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="FlagAlpha/Atom-7B", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("FlagAlpha/Atom-7B", trust_remote_code=True) model = AutoModelForCausalLM.from_pretrained("FlagAlpha/Atom-7B", trust_remote_code=True) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4f438f123092a2fb867aee68c08e6fcf362689a8f535cb9e76dbe40232649d04
- Size of remote file:
- 1.01 MB
- SHA256:
- 04ef61cc08360cd193f9056cb10e26525451fd62759ca714840663257e7bcdd8
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