Serve embedding, reranking, and classification models
LlamaModel
, BertModel
, RobertaModel
or Gemma2Model
, and contain the safetensors, config, tokenizer and sentence-transformer config files.
A good example is the repo BAAI/bge-multilingual-gemma2.
To deploy a model for embeddings, set the following config in your local directory.
config.yaml
in your local directory, you can deploy the model to Baseten.
ForSequenceClassification
suffix in the huggingface repo.
The use-case for these models is either Reward Modeling, Reranking documents in RAG or tasks like content moderation.
Model Repository | Architecture | Function |
---|---|---|
Salesforce/SFR-Embedding-Mistral | MistralModel | embedding |
BAAI/bge-m3 | BertModel | embedding |
BAAI/bge-multilingual-gemma2 | Gemma2Model | embedding |
mixedbread-ai/mxbai-embed-large-v1 | BertModel | embedding |
BAAI/bge-large-en-v1.5 | BertModel | embedding |
allenai/Llama-3.1-Tulu-3-8B-RM | LlamaForSequenceClassification | classifier |
ncbi/MedCPT-Cross-Encoder | BertForSequenceClassification | reranker/classifier |
SamLowe/roberta-base-go_emotions | XLMRobertaForSequenceClassification | classifier |
mixedbread/mxbai-rerank-large-v2-seq | Qwen2ForSequenceClassification | reranker/classifier |
BAAI/bge-en-icl | LlamaModel | embedding |
BAAI/bge-reranker-v2-m3 | BertForSequenceClassification | reranker/classifier |
Skywork/Skywork-Reward-Llama-3.1-8B-v0.2 | LlamaForSequenceClassification | classifier |
Snowflake/snowflake-arctic-embed-l | BertModel | embedding |
nomic-ai/nomic-embed-code | Qwen2Model | embedding |