Instructions to use Aakash010/TRIAL3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Aakash010/TRIAL3 with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="Aakash010/TRIAL3",
	filename="mmproj-FP16.gguf",
)

llm.create_chat_completion(
	messages = "No input example has been defined for this model task."
)

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use Aakash010/TRIAL3 with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf Aakash010/TRIAL3:F16
# Run inference directly in the terminal:
llama-cli -hf Aakash010/TRIAL3:F16

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf Aakash010/TRIAL3:F16
# Run inference directly in the terminal:
llama-cli -hf Aakash010/TRIAL3:F16

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 Aakash010/TRIAL3:F16
# Run inference directly in the terminal:
./llama-cli -hf Aakash010/TRIAL3:F16

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 Aakash010/TRIAL3:F16
# Run inference directly in the terminal:
./build/bin/llama-cli -hf Aakash010/TRIAL3:F16

Use Docker

docker model run hf.co/Aakash010/TRIAL3:F16

LM Studio
Jan
Ollama
How to use Aakash010/TRIAL3 with Ollama:
```
ollama run hf.co/Aakash010/TRIAL3:F16
```

Unsloth Studio new

How to use Aakash010/TRIAL3 with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for Aakash010/TRIAL3 to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for Aakash010/TRIAL3 to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for Aakash010/TRIAL3 to start chatting

Docker Model Runner
How to use Aakash010/TRIAL3 with Docker Model Runner:
```
docker model run hf.co/Aakash010/TRIAL3:F16
```

Lemonade

How to use Aakash010/TRIAL3 with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull Aakash010/TRIAL3:F16

Run and chat with the model

lemonade run user.TRIAL3-F16

List all available models

lemonade list

TRIAL3 / Q8_0

Aakash010

Upload Q8_0 with huggingface_hub

cb0cbeb verified 5 months ago

download

history blame contribute delete

4.13 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:: 53b220c0b3d2a5c3ed52cacb630668bffe441c90a8b5d9be2f5ab2f2a8631d02
Size of remote file:: 4.13 GB
SHA256:: fb400de9ed21d29ea8835aff1ce31e88c3f73d3198b51b5cf0ed43f49a8b627e

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