12 layers, 12 attention heads and 512 token sequence length
The dataset
Multilingual: 10 African languages listed above
143 Million Tokens (1GB of text data)
Tokenizer Vocabulary Size: 70,000 tokens
Intended uses & limitations
afriteva_base
is pre-trained model and primarily aimed at being fine-tuned on multilingual sequence-to-sequence tasks.
>>> from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
>>> tokenizer = AutoTokenizer.from_pretrained("castorini/afriteva_base")
>>> model = AutoModelForSeq2SeqLM.from_pretrained("castorini/afriteva_base")
>>> src_text = "Ó hùn ọ́ láti di ara wa bí?">>> tgt_text = "Would you like to be?">>> model_inputs = tokenizer(src_text, return_tensors="pt")
>>> with tokenizer.as_target_tokenizer():
labels = tokenizer(tgt_text, return_tensors="pt").input_ids
>>> model(**model_inputs, labels=labels) # forward pass
Training Procedure
For information on training procedures, please refer to the AfriTeVa
paper
or
repository
BibTex entry and Citation info
coming soon ...
Runs of castorini afriteva_base on huggingface.co
149
Total runs
-25
24-hour runs
-27
3-day runs
-46
7-day runs
22
30-day runs
More Information About afriteva_base huggingface.co Model
afriteva_base huggingface.co
afriteva_base huggingface.co is an AI model on huggingface.co that provides afriteva_base's model effect (), which can be used instantly with this castorini afriteva_base model. huggingface.co supports a free trial of the afriteva_base model, and also provides paid use of the afriteva_base. Support call afriteva_base model through api, including Node.js, Python, http.
afriteva_base huggingface.co is an online trial and call api platform, which integrates afriteva_base's modeling effects, including api services, and provides a free online trial of afriteva_base, you can try afriteva_base online for free by clicking the link below.
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afriteva_base is an open source model from GitHub that offers a free installation service, and any user can find afriteva_base on GitHub to install. At the same time, huggingface.co provides the effect of afriteva_base install, users can directly use afriteva_base installed effect in huggingface.co for debugging and trial. It also supports api for free installation.