Instructions to use behzatindustries/BehzatOne-8B-A1B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use behzatindustries/BehzatOne-8B-A1B 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 behzatindustries/BehzatOne-8B-A1B:BF16
# Run inference directly in the terminal:
llama cli -hf behzatindustries/BehzatOne-8B-A1B:BF16

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf behzatindustries/BehzatOne-8B-A1B:BF16
# Run inference directly in the terminal:
llama cli -hf behzatindustries/BehzatOne-8B-A1B: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 behzatindustries/BehzatOne-8B-A1B:BF16
# Run inference directly in the terminal:
./llama-cli -hf behzatindustries/BehzatOne-8B-A1B: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 behzatindustries/BehzatOne-8B-A1B:BF16
# Run inference directly in the terminal:
./build/bin/llama-cli -hf behzatindustries/BehzatOne-8B-A1B:BF16

Use Docker

docker model run hf.co/behzatindustries/BehzatOne-8B-A1B:BF16

LM Studio
Jan

vLLM

How to use behzatindustries/BehzatOne-8B-A1B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "behzatindustries/BehzatOne-8B-A1B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "behzatindustries/BehzatOne-8B-A1B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/behzatindustries/BehzatOne-8B-A1B:BF16

Ollama
How to use behzatindustries/BehzatOne-8B-A1B with Ollama:
```
ollama run hf.co/behzatindustries/BehzatOne-8B-A1B:BF16
```

Unsloth Studio

How to use behzatindustries/BehzatOne-8B-A1B 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 behzatindustries/BehzatOne-8B-A1B 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 behzatindustries/BehzatOne-8B-A1B to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for behzatindustries/BehzatOne-8B-A1B to start chatting

Docker Model Runner
How to use behzatindustries/BehzatOne-8B-A1B with Docker Model Runner:
```
docker model run hf.co/behzatindustries/BehzatOne-8B-A1B:BF16
```

Lemonade

How to use behzatindustries/BehzatOne-8B-A1B with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull behzatindustries/BehzatOne-8B-A1B:BF16

Run and chat with the model

lemonade run user.BehzatOne-8B-A1B-BF16

List all available models

lemonade list

Atomic Chat

rebehzat commited on Jul 3

Commit

63f695f

verified ·

1 Parent(s): bad8b1c

Upload BehzatOne v109 GGUF release artifacts

Browse files

Files changed (1) hide show

README.md +10 -10

README.md CHANGED Viewed

@@ -17,9 +17,9 @@ language:
 pipeline_tag: text-generation
 ---
-# BehzatOne-8B-A1B v108
-This is a targeted repair release built on v107. It focuses on strict agentic output contracts: valid unified diffs, complete file rewrites, JSON-only answers, and rejecting tool-schema regurgitation or fake shell transcripts.
 ## Version Lineage
@@ -38,12 +38,12 @@ This is a targeted repair release built on v107. It focuses on strict agentic ou
 ## Artifacts
-- `/v108/` - merged BF16 HF model shards
-- `gguf/BehzatOne-8B-A1B-v108.BF16.gguf` - BF16 GGUF
-- `gguf/BehzatOne-8B-A1B-v108.Q4_K_M.gguf` - Q4_K_M GGUF
-- `Modelfile.v108-bf16`
-- `Modelfile.v108-q4`
-- `Modelfile.v108-agent-q4`
 ## Status
@@ -59,13 +59,13 @@ import torch
 model = AutoModelForCausalLM.from_pretrained(
     "behzatindustries/BehzatOne-8B-A1B",
-    subfolder="v108",
     torch_dtype=torch.bfloat16,
     trust_remote_code=True,
 ).cuda()
 tokenizer = AutoTokenizer.from_pretrained(
     "behzatindustries/BehzatOne-8B-A1B",
-    subfolder="v108",
     trust_remote_code=True,
 )
 ```

 pipeline_tag: text-generation
 ---
+# BehzatOne-8B-A1B v109
+v109 GGUF conversion and Ollama release built from the latest fixed repo Modelfile.
 ## Version Lineage
 ## Artifacts
+- `/v109/` - merged BF16 HF model shards
+- `gguf/BehzatOne-8B-A1B-v109.BF16.gguf` - BF16 GGUF
+- `gguf/BehzatOne-8B-A1B-v109.Q4_K_M.gguf` - Q4_K_M GGUF
+- `Modelfile.v109-bf16`
+- `Modelfile.v109-q4`
+- `Modelfile.v109-agent-q4`
 ## Status
 model = AutoModelForCausalLM.from_pretrained(
     "behzatindustries/BehzatOne-8B-A1B",
+    subfolder="v109",
     torch_dtype=torch.bfloat16,
     trust_remote_code=True,
 ).cuda()
 tokenizer = AutoTokenizer.from_pretrained(
     "behzatindustries/BehzatOne-8B-A1B",
+    subfolder="v109",
     trust_remote_code=True,
 )
 ```