Transformers
PyTorch
TensorBoard
t5
text2text-generation
Generated from Trainer
text-generation-inference
Instructions to use AnushS/Hieroglyph-Translator-Using-Gardiner-Codes with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnushS/Hieroglyph-Translator-Using-Gardiner-Codes with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("AnushS/Hieroglyph-Translator-Using-Gardiner-Codes") model = AutoModelForSeq2SeqLM.from_pretrained("AnushS/Hieroglyph-Translator-Using-Gardiner-Codes", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -22,9 +22,9 @@ To Translate any sequence of hieroglyphs using this model, provide the following
|
|
| 22 |
|
| 23 |
Examples :
|
| 24 |
|
| 25 |
-
"
|
| 26 |
|
| 27 |
-
"Translate hieroglyph
|
| 28 |
|
| 29 |
It achieves the following results on the evaluation set:
|
| 30 |
- Loss: 3.4556
|
|
@@ -55,9 +55,9 @@ The Inference Api on the hugging face model page doesn't work well, load the mod
|
|
| 55 |
|
| 56 |
print(translated_keywords)
|
| 57 |
|
| 58 |
-
print(translated_keywords)
|
| 59 |
|
| 60 |
-
|
|
|
|
| 61 |
|
| 62 |
The Model is intended to be used to translate hieroglyphs. The model does not provide full sentences, it only outputs bits and keywords.
|
| 63 |
|
|
|
|
| 22 |
|
| 23 |
Examples :
|
| 24 |
|
| 25 |
+
"TTranslate hieroglyph gardiner code sequence to English: A4 A5 A1 B6 F8"
|
| 26 |
|
| 27 |
+
"Translate hieroglyph gardiner code sequence to English: A4 A5 G4 H9 P3"
|
| 28 |
|
| 29 |
It achieves the following results on the evaluation set:
|
| 30 |
- Loss: 3.4556
|
|
|
|
| 55 |
|
| 56 |
print(translated_keywords)
|
| 57 |
|
|
|
|
| 58 |
|
| 59 |
+
|
| 60 |
+
# Intended uses & limitations
|
| 61 |
|
| 62 |
The Model is intended to be used to translate hieroglyphs. The model does not provide full sentences, it only outputs bits and keywords.
|
| 63 |
|