Instructions to use sniperyyc/NetFID-PCAP-IP-Header with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sniperyyc/NetFID-PCAP-IP-Header with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="sniperyyc/NetFID-PCAP-IP-Header")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("sniperyyc/NetFID-PCAP-IP-Header") model = AutoModelForMaskedLM.from_pretrained("sniperyyc/NetFID-PCAP-IP-Header") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:055f6ecb8e33ad2b2d5c1dc9329cdff2f89dcc2101f4b5517b5ba8c193b0df45
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size 438085208
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