Text Classification
Transformers
Safetensors
GGUF
English
Hindi
Bengali
modernbert
emoji
emoji-prediction
tone-classification
on-device
llama-cpp
code-mixed
hinglish
banglish
text-embeddings-inference
feature-extraction
Instructions to use subhadeep3902/emojet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- 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
Download tokenizer_config.json from subhadeep3902/emojet: direct link, hf CLI and curl.
- Browser
- Download file 379 Bytes
-
https://huggingface.co/subhadeep3902/emojet/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://subhadeep3902/emojet/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/subhadeep3902/emojet/resolve/main/tokenizer_config.json
379 Bytes
| { | |
| "backend": "tokenizers", | |
| "clean_up_tokenization_spaces": true, | |
| "cls_token": "[CLS]", | |
| "is_local": true, | |
| "local_files_only": false, | |
| "mask_token": "[MASK]", | |
| "model_input_names": [ | |
| "input_ids", | |
| "attention_mask" | |
| ], | |
| "model_max_length": 8192, | |
| "pad_token": "[PAD]", | |
| "sep_token": "[SEP]", | |
| "tokenizer_class": "TokenizersBackend", | |
| "unk_token": "[UNK]" | |
| } | |