- Libraries
- Transformers
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") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use subhadeep3902/emojet with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible embeddings server:
llama serve -hf subhadeep3902/emojet:F16 --embeddings
Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible embeddings server:
llama serve -hf subhadeep3902/emojet:F16 --embeddings
Build from source code
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
- Llama new
- LM Studio
- Jan
- Ollama
How to use subhadeep3902/emojet with Ollama:
ollama run hf.co/subhadeep3902/emojet:F16
- Unsloth Desktop
- Docker Model Runner
How to use subhadeep3902/emojet with Docker Model Runner:
docker model run hf.co/subhadeep3902/emojet:F16
- Lemonade
How to use subhadeep3902/emojet with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/
lemonade pull subhadeep3902/emojet:F16
Run and chat with the model
lemonade run user.emojet-F16
List all available models
lemonade list
- Atomic Chat
