Text Classification
Transformers
Safetensors
GGUF
English
bert
email
triage
classification
specific-ai
text-embeddings-inference
feature-extraction
Instructions to use specific-AI/email-agent-triage with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use specific-AI/email-agent-triage with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="specific-AI/email-agent-triage")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("specific-AI/email-agent-triage") model = AutoModelForSequenceClassification.from_pretrained("specific-AI/email-agent-triage", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use specific-AI/email-agent-triage with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf specific-AI/email-agent-triage # Run inference directly in the terminal: llama cli -hf specific-AI/email-agent-triage
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf specific-AI/email-agent-triage # Run inference directly in the terminal: llama cli -hf specific-AI/email-agent-triage
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf specific-AI/email-agent-triage # Run inference directly in the terminal: ./llama-cli -hf specific-AI/email-agent-triage
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf specific-AI/email-agent-triage # Run inference directly in the terminal: ./build/bin/llama-cli -hf specific-AI/email-agent-triage
Use Docker
docker model run hf.co/specific-AI/email-agent-triage
- LM Studio
- Jan
- Ollama
How to use specific-AI/email-agent-triage with Ollama:
ollama run hf.co/specific-AI/email-agent-triage
- Unsloth Desktop
- Docker Model Runner
How to use specific-AI/email-agent-triage with Docker Model Runner:
docker model run hf.co/specific-AI/email-agent-triage
- Lemonade
How to use specific-AI/email-agent-triage with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull specific-AI/email-agent-triage
Run and chat with the model
lemonade run user.email-agent-triage-{{QUANT_TAG}}List all available models
lemonade list
- Atomic Chat
Download classifier_b.npy from specific-AI/email-agent-triage: direct link, hf CLI and curl.
- Browser
- Download file 148 Bytes
-
https://huggingface.co/specific-AI/email-agent-triage/resolve/main/classifier_b.npy
- Command line
-
hf download hf://specific-AI/email-agent-triage/classifier_b.npy
-
curl -L -o classifier_b.npy https://huggingface.co/specific-AI/email-agent-triage/resolve/main/classifier_b.npy
148 Bytes
- Xet hash:
- 41b9af4c16b37616e286fea1525d1866d11d7e0b5dba35e0a8d39e3bdcbb9df0
- Size of remote file:
- 148 Bytes
- SHA256:
- b21fd125724bcfb3ca4642cd379f1fde48418883c0bc5e764f91064e3316143a
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