Instructions to use selorahomes/Selora-AI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use selorahomes/Selora-AI with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="selorahomes/Selora-AI")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("selorahomes/Selora-AI", dtype="auto")

llama-cpp-python

How to use selorahomes/Selora-AI with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="selorahomes/Selora-AI",
	filename="qwen3_17b_base.Q6_K.gguf",
)

llm.create_chat_completion(
	messages = [
		{
			"role": "user",
			"content": "What is the capital of France?"
		}
	]
)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use selorahomes/Selora-AI with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf selorahomes/Selora-AI:Q6_K
# Run inference directly in the terminal:
llama-cli -hf selorahomes/Selora-AI:Q6_K

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf selorahomes/Selora-AI:Q6_K
# Run inference directly in the terminal:
llama-cli -hf selorahomes/Selora-AI:Q6_K

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 selorahomes/Selora-AI:Q6_K
# Run inference directly in the terminal:
./llama-cli -hf selorahomes/Selora-AI:Q6_K

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 selorahomes/Selora-AI:Q6_K
# Run inference directly in the terminal:
./build/bin/llama-cli -hf selorahomes/Selora-AI:Q6_K

Use Docker

docker model run hf.co/selorahomes/Selora-AI:Q6_K

LM Studio
Jan

vLLM

How to use selorahomes/Selora-AI with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "selorahomes/Selora-AI"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "selorahomes/Selora-AI",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/selorahomes/Selora-AI:Q6_K

SGLang

How to use selorahomes/Selora-AI with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "selorahomes/Selora-AI" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "selorahomes/Selora-AI",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "selorahomes/Selora-AI" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "selorahomes/Selora-AI",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Ollama
How to use selorahomes/Selora-AI with Ollama:
```
ollama run hf.co/selorahomes/Selora-AI:Q6_K
```

Unsloth Studio

How to use selorahomes/Selora-AI 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 selorahomes/Selora-AI 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 selorahomes/Selora-AI to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for selorahomes/Selora-AI to start chatting

How to use selorahomes/Selora-AI with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf selorahomes/Selora-AI:Q6_K

Configure the model in Pi

# Install Pi:
npm install -g @mariozechner/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "selorahomes/Selora-AI:Q6_K"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use selorahomes/Selora-AI with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf selorahomes/Selora-AI:Q6_K

Configure Hermes

# Install Hermes:
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
hermes setup
# Point Hermes at the local server:
hermes config set model.provider custom
hermes config set model.base_url http://127.0.0.1:8080/v1
hermes config set model.default selorahomes/Selora-AI:Q6_K

Run Hermes

hermes

Atomic Chat new
Docker Model Runner
How to use selorahomes/Selora-AI with Docker Model Runner:
```
docker model run hf.co/selorahomes/Selora-AI:Q6_K
```

Lemonade

How to use selorahomes/Selora-AI with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull selorahomes/Selora-AI:Q6_K

Run and chat with the model

lemonade run user.Selora-AI-Q6_K

List all available models

lemonade list

lafoush commited on 19 days ago

Commit

8423079

verified ·

1 Parent(s): 7ace5ac

Publish selora-ai-local 0.4.3

Browse files

Files changed (8) hide show

.gitattributes +5 -0
manifest.json +15 -11
qwen3_17b_base.f16.gguf +0 -3
selora-v042-answer.f16.gguf → selora-v043-answer.f16.gguf +1 -1
selora-v042-automation.f16.gguf → selora-v043-automation.f16.gguf +1 -1
selora-v042-clarification.f16.gguf → selora-v043-clarification.f16.gguf +0 -0
selora-v042-command.f16.gguf → selora-v043-command.f16.gguf +1 -1
selora-v043-recipe.f16.gguf +3 -0

.gitattributes CHANGED Viewed

@@ -48,3 +48,8 @@ selora-v042-answer.f16.gguf filter=lfs diff=lfs merge=lfs -text
 selora-v042-automation.f16.gguf filter=lfs diff=lfs merge=lfs -text
 selora-v042-clarification.f16.gguf filter=lfs diff=lfs merge=lfs -text
 selora-v042-command.f16.gguf filter=lfs diff=lfs merge=lfs -text

 selora-v042-automation.f16.gguf filter=lfs diff=lfs merge=lfs -text
 selora-v042-clarification.f16.gguf filter=lfs diff=lfs merge=lfs -text
 selora-v042-command.f16.gguf filter=lfs diff=lfs merge=lfs -text
+selora-v043-answer.f16.gguf filter=lfs diff=lfs merge=lfs -text
+selora-v043-automation.f16.gguf filter=lfs diff=lfs merge=lfs -text
+selora-v043-clarification.f16.gguf filter=lfs diff=lfs merge=lfs -text
+selora-v043-command.f16.gguf filter=lfs diff=lfs merge=lfs -text
+selora-v043-recipe.f16.gguf filter=lfs diff=lfs merge=lfs -text

manifest.json CHANGED Viewed

@@ -37,27 +37,31 @@
       "size": 676
     },
     "qwen3_17b_base.f16.gguf": {
-      "sha256": "3e4009f0d96955a45f29aa77bded839d376d7832823c6909f76c84ace81dc445",
-      "size": 4069678880
     },
-    "selora-v042-answer.f16.gguf": {
-      "sha256": "7d5a7dea12fac72aebc1fb361d18e97e46172a8c2f5cf0c7968322167ef272f9",
       "size": 14957792
     },
-    "selora-v042-automation.f16.gguf": {
-      "sha256": "6ceb555a2a809b54294bf311474286612b18a1870789575f3ed9d49396adff3d",
       "size": 37374880
     },
-    "selora-v042-clarification.f16.gguf": {
       "sha256": "69d547c8175412a9dc52fdce22dc45cc3cb448e4eb05f11d73e9a27c8939bbe0",
       "size": 9977056
     },
-    "selora-v042-command.f16.gguf": {
-      "sha256": "7555c5ee00ed46a1eef829d8e82d22ecc251502650c9e866e78c5d0b65e2e1d4",
       "size": 19938528
     }
   },
   "base_model": "Qwen/Qwen3-1.7B",
-  "released_at": "2026-05-14T15:16:49Z",
-  "version": "0.4.2"
 }

       "size": 676
     },
     "qwen3_17b_base.f16.gguf": {
+      "sha256": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855",
+      "size": 0
     },
+    "selora-v043-answer.f16.gguf": {
+      "sha256": "1eef5f6077ceec6af0cfa4ec9ebd1a0267d7c7ea9593a3cfbde8aba3b04906c4",
       "size": 14957792
     },
+    "selora-v043-automation.f16.gguf": {
+      "sha256": "06d9e6d0ae56ea4a085875183523195272629e6b735bc376738f1104bda4f743",
       "size": 37374880
     },
+    "selora-v043-clarification.f16.gguf": {
       "sha256": "69d547c8175412a9dc52fdce22dc45cc3cb448e4eb05f11d73e9a27c8939bbe0",
       "size": 9977056
     },
+    "selora-v043-command.f16.gguf": {
+      "sha256": "3687dd48a5495a9808271f6371ba0290512a0b91e5a70fd3d1d55437544cb0d0",
       "size": 19938528
+    },
+    "selora-v043-recipe.f16.gguf": {
+      "sha256": "51beb4bae22550d15ddafd44f19e76adbf975c796ed4fb4aa0622b62d2561173",
+      "size": 37374880
     }
   },
   "base_model": "Qwen/Qwen3-1.7B",
+  "released_at": "2026-05-22T03:16:26Z",
+  "version": "0.4.3"
 }

qwen3_17b_base.f16.gguf CHANGED Viewed

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:3e4009f0d96955a45f29aa77bded839d376d7832823c6909f76c84ace81dc445
-size 4069678880

selora-v042-answer.f16.gguf → selora-v043-answer.f16.gguf RENAMED Viewed

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:7d5a7dea12fac72aebc1fb361d18e97e46172a8c2f5cf0c7968322167ef272f9
 size 14957792

 version https://git-lfs.github.com/spec/v1
+oid sha256:1eef5f6077ceec6af0cfa4ec9ebd1a0267d7c7ea9593a3cfbde8aba3b04906c4
 size 14957792

selora-v042-automation.f16.gguf → selora-v043-automation.f16.gguf RENAMED Viewed

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:6ceb555a2a809b54294bf311474286612b18a1870789575f3ed9d49396adff3d
 size 37374880

 version https://git-lfs.github.com/spec/v1
+oid sha256:06d9e6d0ae56ea4a085875183523195272629e6b735bc376738f1104bda4f743
 size 37374880

selora-v042-clarification.f16.gguf → selora-v043-clarification.f16.gguf RENAMED Viewed

File without changes

selora-v042-command.f16.gguf → selora-v043-command.f16.gguf RENAMED Viewed

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:7555c5ee00ed46a1eef829d8e82d22ecc251502650c9e866e78c5d0b65e2e1d4
 size 19938528

 version https://git-lfs.github.com/spec/v1
+oid sha256:3687dd48a5495a9808271f6371ba0290512a0b91e5a70fd3d1d55437544cb0d0
 size 19938528

selora-v043-recipe.f16.gguf ADDED Viewed

	@@ -0,0 +1,3 @@

+version https://git-lfs.github.com/spec/v1
+oid sha256:51beb4bae22550d15ddafd44f19e76adbf975c796ed4fb4aa0622b62d2561173
+size 37374880