Model reference · open weights

ConGen-WangchanBERT-Small

Available as managed deployment Embeddings kornwtp · community Embeddings 1 variants 650 dl/mo

ConGen-WangchanBERT-Small is an open-weight embedding model from kornwtp. AxForge deploys and operates it for you on dedicated EU-owned hardware — with the licence handled where one is required.

Available as managed deployment — configured and operated for you on dedicated EU hardware, quoted per deployment.

What it is

Released bykornwtp
TypeEmbedding models
TaskEmbeddings
Context512 tokens
Runs withsentence-transformers
Released2023-05-11
Popularity650 downloads / month
LicenceOpen weights

About

What ConGen-WangchanBERT-Small is

This is a ConGen model: It maps sentences to a 128 dimensional dense vector space and can be used for tasks like semantic search.

Read the full model card

Usage

Using this model becomes easy when you have ConGen installed:

pip install -U git+https://github.com/KornWtp/ConGen.git

Then you can use the model like this:

from sentence_transformers import SentenceTransformer
sentences = ["กลุ่มผู้ชายเล่นฟุตบอลบนชายหาด", "กลุ่มเด็กชายกำลังเล่นฟุตบอลบนชายหาด"]

model = SentenceTransformer('kornwtp/ConGen-WangchanBERT-Small')
embeddings = model.encode(sentences)
print(embeddings)

Evaluation Results

For an automated evaluation of this model, see the Thai Sentence Embeddings Benchmark: Semantic Textual Similarity

Citing & Authors

@inproceedings{limkonchotiwat-etal-2022-congen,
    title = "{ConGen}: Unsupervised Control and Generalization Distillation For Sentence Representation",
    author = "Limkonchotiwat, Peerat  and
      Ponwitayarat, Wuttikorn  and
      Lowphansirikul, Lalita and
      Udomcharoenchaikit, Can  and
      Chuangsuwanich, Ekapol  and
      Nutanong, Sarana",
    booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2022",
    year = "2022",
    publisher = "Association for Computational Linguistics",
}

From the published model card. Full card on the HuggingFace links in the sidebar.

Using it via the API

Call it like any OpenAI endpoint

Once AxForge deploys congen-wangchanbert-small for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (congen-wangchanbert-small below is illustrative; you get the exact model name on deployment.)

$ curl -sS https://api.axforge.ai/v1/embeddings \
  -H "Authorization: Bearer $AXFORGE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"congen-wangchanbert-small","input":"text to embed"}'

Create an account — your API key is available in the console. 3M free tokens every 30 days with every new account.

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