Instructions to use abhijitkumarjha88192/cs_repl_ai_alpaca_lora_gemma2_2b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use abhijitkumarjha88192/cs_repl_ai_alpaca_lora_gemma2_2b with Transformers:

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("abhijitkumarjha88192/cs_repl_ai_alpaca_lora_gemma2_2b", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use abhijitkumarjha88192/cs_repl_ai_alpaca_lora_gemma2_2b 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 abhijitkumarjha88192/cs_repl_ai_alpaca_lora_gemma2_2b:BF16
# Run inference directly in the terminal:
llama cli -hf abhijitkumarjha88192/cs_repl_ai_alpaca_lora_gemma2_2b:BF16

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf abhijitkumarjha88192/cs_repl_ai_alpaca_lora_gemma2_2b:BF16
# Run inference directly in the terminal:
llama cli -hf abhijitkumarjha88192/cs_repl_ai_alpaca_lora_gemma2_2b:BF16

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 abhijitkumarjha88192/cs_repl_ai_alpaca_lora_gemma2_2b:BF16
# Run inference directly in the terminal:
./llama-cli -hf abhijitkumarjha88192/cs_repl_ai_alpaca_lora_gemma2_2b:BF16

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 abhijitkumarjha88192/cs_repl_ai_alpaca_lora_gemma2_2b:BF16
# Run inference directly in the terminal:
./build/bin/llama-cli -hf abhijitkumarjha88192/cs_repl_ai_alpaca_lora_gemma2_2b:BF16

Use Docker

docker model run hf.co/abhijitkumarjha88192/cs_repl_ai_alpaca_lora_gemma2_2b:BF16

LM Studio
Jan
Ollama
How to use abhijitkumarjha88192/cs_repl_ai_alpaca_lora_gemma2_2b with Ollama:
```
ollama run hf.co/abhijitkumarjha88192/cs_repl_ai_alpaca_lora_gemma2_2b:BF16
```
Unsloth Desktop
Docker Model Runner
How to use abhijitkumarjha88192/cs_repl_ai_alpaca_lora_gemma2_2b with Docker Model Runner:
```
docker model run hf.co/abhijitkumarjha88192/cs_repl_ai_alpaca_lora_gemma2_2b:BF16
```

Lemonade

How to use abhijitkumarjha88192/cs_repl_ai_alpaca_lora_gemma2_2b with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull abhijitkumarjha88192/cs_repl_ai_alpaca_lora_gemma2_2b:BF16

Run and chat with the model

lemonade run user.cs_repl_ai_alpaca_lora_gemma2_2b-BF16

List all available models

lemonade list

Atomic Chat

cs_repl_ai_alpaca_lora_gemma2_2b / unsloth.Q4_K_M.gguf

abhijitkumarjha88192

Upload folder using huggingface_hub

1fee67b verified about 2 years ago

Download

History Blame GGUF Editor new Delete

1.71 GB

This file is stored with Xet . It is too big to display, but you can still download it.

Xet Pointer Details

( Raw pointer file )

Xet hash:: ef45bd3f38584f60060bb2ce0ffa5217dce723c6eb3e1f111217535a8fd823ae
Size of remote file:: 1.71 GB
SHA256:: df8b9b3e7cc51625b8941cf19aa86bfcfe72c80589cb2951e72195df1fdefc72

Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.