Text Generation
Safetensors
GGUF
Hindi
English
gemma2
agriculture
farming
india
gemma
text-generation-inference
conversational
unsloth
Instructions to use bf369/BeejX-Gemma2-2B-Hindi-SFT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use bf369/BeejX-Gemma2-2B-Hindi-SFT 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 bf369/BeejX-Gemma2-2B-Hindi-SFT:Q4_K_M # Run inference directly in the terminal: llama cli -hf bf369/BeejX-Gemma2-2B-Hindi-SFT:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf bf369/BeejX-Gemma2-2B-Hindi-SFT:Q4_K_M # Run inference directly in the terminal: llama cli -hf bf369/BeejX-Gemma2-2B-Hindi-SFT:Q4_K_M
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 bf369/BeejX-Gemma2-2B-Hindi-SFT:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf bf369/BeejX-Gemma2-2B-Hindi-SFT:Q4_K_M
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 bf369/BeejX-Gemma2-2B-Hindi-SFT:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf bf369/BeejX-Gemma2-2B-Hindi-SFT:Q4_K_M
Use Docker
docker model run hf.co/bf369/BeejX-Gemma2-2B-Hindi-SFT:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use bf369/BeejX-Gemma2-2B-Hindi-SFT with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "bf369/BeejX-Gemma2-2B-Hindi-SFT" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "bf369/BeejX-Gemma2-2B-Hindi-SFT", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/bf369/BeejX-Gemma2-2B-Hindi-SFT:Q4_K_M
- Ollama
How to use bf369/BeejX-Gemma2-2B-Hindi-SFT with Ollama:
ollama run hf.co/bf369/BeejX-Gemma2-2B-Hindi-SFT:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use bf369/BeejX-Gemma2-2B-Hindi-SFT with Docker Model Runner:
docker model run hf.co/bf369/BeejX-Gemma2-2B-Hindi-SFT:Q4_K_M
- Lemonade
How to use bf369/BeejX-Gemma2-2B-Hindi-SFT with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull bf369/BeejX-Gemma2-2B-Hindi-SFT:Q4_K_M
Run and chat with the model
lemonade run user.BeejX-Gemma2-2B-Hindi-SFT-Q4_K_M
List all available models
lemonade list
- Atomic Chat
Download special_tokens_map.json from bf369/BeejX-Gemma2-2B-Hindi-SFT: direct link, hf CLI and curl.
- Browser
- Download file 636 Bytes
-
https://huggingface.co/bf369/BeejX-Gemma2-2B-Hindi-SFT/resolve/main/special_tokens_map.json
- Command line
-
hf download hf://bf369/BeejX-Gemma2-2B-Hindi-SFT/special_tokens_map.json
-
curl -L -o special_tokens_map.json https://huggingface.co/bf369/BeejX-Gemma2-2B-Hindi-SFT/resolve/main/special_tokens_map.json
636 Bytes
| { | |
| "additional_special_tokens": [ | |
| "<start_of_turn>", | |
| "<end_of_turn>" | |
| ], | |
| "bos_token": { | |
| "content": "<bos>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false | |
| }, | |
| "eos_token": { | |
| "content": "<eos>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false | |
| }, | |
| "pad_token": { | |
| "content": "<pad>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false | |
| }, | |
| "unk_token": { | |
| "content": "<unk>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false | |
| } | |
| } | |