Instructions to use ManojAlexender/Final_layer_LM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ManojAlexender/Final_layer_LM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ManojAlexender/Final_layer_LM")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ManojAlexender/Final_layer_LM") model = AutoModelForSequenceClassification.from_pretrained("ManojAlexender/Final_layer_LM", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-5500/optimizer.pt from ManojAlexender/Final_layer_LM: direct link, hf CLI and curl.
- Browser
- Download file 997 MB
-
https://huggingface.co/ManojAlexender/Final_layer_LM/resolve/main/checkpoint-5500/optimizer.pt
- Command line
-
hf download hf://ManojAlexender/Final_layer_LM/checkpoint-5500/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/ManojAlexender/Final_layer_LM/resolve/main/checkpoint-5500/optimizer.pt
997 MB
- Xet hash:
- 264fbb7a03cb2fdf56b3904faf0b6a864f40e48bad53d14764e52bddab8dfb78
- Size of remote file:
- 997 MB
- SHA256:
- 8f0c2927b3cb22f9dabba616c516bf45ca43eaafd2a8dd3f3d61e82c62af9d22
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