Text Classification
Transformers
Safetensors
llama
Generated from Trainer
trl
reward-trainer
text-embeddings-inference
Instructions to use sergak0/trainer_output with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sergak0/trainer_output with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="sergak0/trainer_output")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("sergak0/trainer_output") model = AutoModelForSequenceClassification.from_pretrained("sergak0/trainer_output", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from sergak0/trainer_output: direct link, hf CLI and curl.
- Browser
- Download file 6.03 kB
-
https://huggingface.co/sergak0/trainer_output/resolve/main/training_args.bin
- Command line
-
hf download hf://sergak0/trainer_output/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/sergak0/trainer_output/resolve/main/training_args.bin
6.03 kB
- Xet hash:
- 3fea65784225407c7441b6d57dad4bfa7d7e5b46455cc64e59d554d8b20488ae
- Size of remote file:
- 6.03 kB
- SHA256:
- 2c1c98c5b65a67b76d339b2cfac46deace4798bc9293b0d930bd62de14bc9707
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