Instructions to use lancehar/mean_layernorm_linear_seed6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lancehar/mean_layernorm_linear_seed6 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="lancehar/mean_layernorm_linear_seed6", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForSequenceClassification model = AutoModelForSequenceClassification.from_pretrained("lancehar/mean_layernorm_linear_seed6", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from lancehar/mean_layernorm_linear_seed6: direct link, hf CLI and curl.
- Browser
- Download file 4.88 kB
-
https://huggingface.co/lancehar/mean_layernorm_linear_seed6/resolve/main/training_args.bin
- Command line
-
hf download hf://lancehar/mean_layernorm_linear_seed6/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/lancehar/mean_layernorm_linear_seed6/resolve/main/training_args.bin
4.88 kB
- Xet hash:
- 0c40df6c439bb9f5ea88e878955ff149ed402627183b7c6946678f05acbe7a16
- Size of remote file:
- 4.88 kB
- SHA256:
- 15d17db566d266013af03a48da12b993aa2b485f122344645b19641417f7840d
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