Transformers
PyTorch
ONNX
Safetensors
bart
text2text-generation
Generated from Trainer
alpaca
self-instruct
instruction generation
instructiongen
Eval Results (legacy)
Instructions to use pszemraj/bart-base-instructiongen with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pszemraj/bart-base-instructiongen with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("pszemraj/bart-base-instructiongen") model = AutoModelForSeq2SeqLM.from_pretrained("pszemraj/bart-base-instructiongen", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download eval_results.json from pszemraj/bart-base-instructiongen: direct link, hf CLI and curl.
- Browser
- Download file 343 Bytes
-
https://huggingface.co/pszemraj/bart-base-instructiongen/resolve/main/eval_results.json
- Command line
-
hf download hf://pszemraj/bart-base-instructiongen/eval_results.json
-
curl -L -o eval_results.json https://huggingface.co/pszemraj/bart-base-instructiongen/resolve/main/eval_results.json
343 Bytes
| { | |
| "epoch": 2.0, | |
| "eval_gen_len": 14.317864619678994, | |
| "eval_loss": 1.003404140472412, | |
| "eval_rouge1": 61.7209, | |
| "eval_rouge2": 45.0116, | |
| "eval_rougeL": 59.8188, | |
| "eval_rougeLsum": 59.8931, | |
| "eval_runtime": 267.2118, | |
| "eval_samples": 2866, | |
| "eval_samples_per_second": 10.726, | |
| "eval_steps_per_second": 10.726 | |
| } |