Instructions to use Fluospark128/Model1111 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Fluospark128/Model1111 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Fluospark128/Model1111")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Fluospark128/Model1111", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Download README.md from Fluospark128/Model1111: direct link, hf CLI and curl.
- Browser
- Download file 235 Bytes
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https://huggingface.co/Fluospark128/Model1111/resolve/main/README.md
- Command line
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hf download hf://Fluospark128/Model1111/README.md
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curl -L -o README.md https://huggingface.co/Fluospark128/Model1111/resolve/main/README.md
235 Bytes
metadata
datasets:
- amphion/Emilia-Dataset
language:
- en
metrics:
- bertscore
base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
pipeline_tag: text-classification
library_name: transformers
tags:
- legal
- finance
- climate
- chemistry