Instructions to use aaro765/BanBTPV4-coder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use aaro765/BanBTPV4-coder with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="aaro765/BanBTPV4-coder",
	filename="BanBTPV4-coder/banbtpv4-coder.gguf",
)

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

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use aaro765/BanBTPV4-coder with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf aaro765/BanBTPV4-coder
# Run inference directly in the terminal:
llama-cli -hf aaro765/BanBTPV4-coder

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf aaro765/BanBTPV4-coder
# Run inference directly in the terminal:
llama-cli -hf aaro765/BanBTPV4-coder

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 aaro765/BanBTPV4-coder
# Run inference directly in the terminal:
./llama-cli -hf aaro765/BanBTPV4-coder

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 aaro765/BanBTPV4-coder
# Run inference directly in the terminal:
./build/bin/llama-cli -hf aaro765/BanBTPV4-coder

Use Docker

docker model run hf.co/aaro765/BanBTPV4-coder

LM Studio
Jan
Ollama
How to use aaro765/BanBTPV4-coder with Ollama:
```
ollama run hf.co/aaro765/BanBTPV4-coder
```

Unsloth Studio

How to use aaro765/BanBTPV4-coder 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 aaro765/BanBTPV4-coder 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 aaro765/BanBTPV4-coder to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for aaro765/BanBTPV4-coder to start chatting

Docker Model Runner
How to use aaro765/BanBTPV4-coder with Docker Model Runner:
```
docker model run hf.co/aaro765/BanBTPV4-coder
```

Lemonade

How to use aaro765/BanBTPV4-coder with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull aaro765/BanBTPV4-coder

Run and chat with the model

lemonade run user.BanBTPV4-coder-{{QUANT_TAG}}

List all available models

lemonade list

aaro765 commited on 28 days ago

Commit

a947f95

verified ·

1 Parent(s): db32468

Update README.md

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@@ -1,3 +1,14 @@
----
-license: apache-2.0
----

+---
+license: apache-2.0
+---
+BanBTP V4-coder
+Welcome! BanBTPV4 is built on the same base as V3 of BanBTP BUT this model is specifically for coding alone.
+This model's motto is "A good model for coding". however, this model has a secret. it believes it is a 100T parameter model. Maybe it is, maybe it isn't. 🤫
+The reality is, this model is based on Gemma4 E2B finetuned on deepseepseekv4-8000x dataset. This allows it to be good at reasoning tasks and specifically, coding tasks too.
+BanBTP V4-coder is designed to be a less restricted version of BanBTP V3. It is the same V3 but finetuned on deepseekv4-8000x dataset. However, this model is not good at following BanBTP V3 system prompt, so we utilize a smaller prompt that gives you the essence of BanBTP V3.
+This model is specifically designed for coding ALONE though. But it can reason well too. This model though focuses only on coding.