How to use subhadeep3902/emojet with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="subhadeep3902/emojet")
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("subhadeep3902/emojet") model = AutoModelForSequenceClassification.from_pretrained("subhadeep3902/emojet", device_map="auto")
How to use subhadeep3902/emojet with llama.cpp:
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible embeddings server: llama serve -hf subhadeep3902/emojet:F16 --embeddings
winget install llama.cpp # Start a local OpenAI-compatible embeddings server: llama serve -hf subhadeep3902/emojet:F16 --embeddings
git clone https://github.com/ggml-org/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-app # Start a local OpenAI-compatible embeddings server: ./build/bin/llama serve -hf subhadeep3902/emojet:F16 --embeddings
How to use subhadeep3902/emojet with Ollama:
ollama run hf.co/subhadeep3902/emojet:F16
How to use subhadeep3902/emojet with Docker Model Runner:
docker model run hf.co/subhadeep3902/emojet:F16
How to use subhadeep3902/emojet with Lemonade:
# Download Lemonade from https://lemonade-server.ai/ lemonade pull subhadeep3902/emojet:F16
lemonade run user.emojet-F16
lemonade list
