Instructions to use EthioNLP/EthioLLM-b-70k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use EthioNLP/EthioLLM-b-70k with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="EthioNLP/EthioLLM-b-70k")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("EthioNLP/EthioLLM-b-70k") model = AutoModelForMaskedLM.from_pretrained("EthioNLP/EthioLLM-b-70k", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download eval_results.json from EthioNLP/EthioLLM-b-70k: direct link, hf CLI and curl.
- Browser
- Download file 229 Bytes
-
https://huggingface.co/EthioNLP/EthioLLM-b-70k/resolve/main/eval_results.json
- Command line
-
hf download hf://EthioNLP/EthioLLM-b-70k/eval_results.json
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curl -L -o eval_results.json https://huggingface.co/EthioNLP/EthioLLM-b-70k/resolve/main/eval_results.json
229 Bytes
| { | |
| "epoch": 10.0, | |
| "eval_loss": 3.161780834197998, | |
| "eval_runtime": 2455.7469, | |
| "eval_samples": 181215, | |
| "eval_samples_per_second": 73.792, | |
| "eval_steps_per_second": 3.075, | |
| "perplexity": 23.612608650107834 | |
| } |