Instructions to use MHGanainy/gpt2-xl-lora-ecthr-random-imbalanced-uniform-cluster-8-id-0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use MHGanainy/gpt2-xl-lora-ecthr-random-imbalanced-uniform-cluster-8-id-0 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("openai-community/gpt2-xl") model = PeftModel.from_pretrained(base_model, "MHGanainy/gpt2-xl-lora-ecthr-random-imbalanced-uniform-cluster-8-id-0") - Notebooks
- Google Colab
- Kaggle
Download eval_results.json from MHGanainy/gpt2-xl-lora-ecthr-random-imbalanced-uniform-cluster-8-id-0: direct link, hf CLI and curl.
- Browser
- Download file 197 Bytes
-
https://huggingface.co/MHGanainy/gpt2-xl-lora-ecthr-random-imbalanced-uniform-cluster-8-id-0/resolve/main/eval_results.json
- Command line
-
hf download hf://MHGanainy/gpt2-xl-lora-ecthr-random-imbalanced-uniform-cluster-8-id-0/eval_results.json
-
curl -L -o eval_results.json https://huggingface.co/MHGanainy/gpt2-xl-lora-ecthr-random-imbalanced-uniform-cluster-8-id-0/resolve/main/eval_results.json
197 Bytes
| { | |
| "epoch": 1.0, | |
| "eval_loss": 2.0968925952911377, | |
| "eval_runtime": 9.7787, | |
| "eval_samples_per_second": 22.293, | |
| "eval_steps_per_second": 2.863, | |
| "perplexity": 8.140833703043482 | |
| } |