Instructions to use banjl4487/MODEL with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use banjl4487/MODEL with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="banjl4487/MODEL",
	filename="jarvis_model.gguf",
)

output = llm(
	"Once upon a time,",
	max_tokens=512,
	echo=True
)
print(output)

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use banjl4487/MODEL with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf banjl4487/MODEL
# Run inference directly in the terminal:
llama-cli -hf banjl4487/MODEL

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf banjl4487/MODEL
# Run inference directly in the terminal:
llama-cli -hf banjl4487/MODEL

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 banjl4487/MODEL
# Run inference directly in the terminal:
./llama-cli -hf banjl4487/MODEL

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 banjl4487/MODEL
# Run inference directly in the terminal:
./build/bin/llama-cli -hf banjl4487/MODEL

Use Docker

docker model run hf.co/banjl4487/MODEL

LM Studio
Jan
Ollama
How to use banjl4487/MODEL with Ollama:
```
ollama run hf.co/banjl4487/MODEL
```

Unsloth Studio new

How to use banjl4487/MODEL 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 banjl4487/MODEL 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 banjl4487/MODEL to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for banjl4487/MODEL to start chatting

Docker Model Runner
How to use banjl4487/MODEL with Docker Model Runner:
```
docker model run hf.co/banjl4487/MODEL
```

Lemonade

How to use banjl4487/MODEL with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull banjl4487/MODEL

Run and chat with the model

lemonade run user.MODEL-{{QUANT_TAG}}

List all available models

lemonade list

banjl4487 commited on 10 days ago

Commit

db472ea

verified ·

1 Parent(s): 3e4b546

Upload jarvis_model.gguf with huggingface_hub

Browse files

Files changed (2) hide show

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jarvis_model.gguf +3 -0

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@@ -36,3 +36,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 Bllossom-3B-Bias-Detector/tokenizer.json filter=lfs diff=lfs merge=lfs -text
 asd/tokenizer.json filter=lfs diff=lfs merge=lfs -text
 k_trend_master_engine/tokenizer.json filter=lfs diff=lfs merge=lfs -text

 Bllossom-3B-Bias-Detector/tokenizer.json filter=lfs diff=lfs merge=lfs -text
 asd/tokenizer.json filter=lfs diff=lfs merge=lfs -text
 k_trend_master_engine/tokenizer.json filter=lfs diff=lfs merge=lfs -text
+jarvis_model.gguf filter=lfs diff=lfs merge=lfs -text

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