HERMES
GGUF
English
llm-routing
model-chooser
intelligent-orchestration
modernbert
fine-tuned
cma-es
federated-learning
cost-optimization
open-source
production-ai
model-dispatch
prompt-routing
multi-model
ensemble-decision
human-readable-decisions
federated-llm
evolution-strategy
ai-infrastructure
llm-inference
prompt-classification
model-selection
intelligent-dispatch
cost-effective-llm
production-routing
free-llm-api
openrouter
transformer-based
classifier
v1.3.0
fugusashi
eulogik
self-hosted
on-device
cpu-inference
low-latency
83ms-inference
3-model-classes
gpt-oss
lfm
149m-params
cross-entropy-training
cosine-scheduler
differential-privacy
federated-averaging
multi-agent
task-orchestration
grpo-reinforcement-learning
human-in-the-loop
explainable-ai
xai
interpretable-ai
natural-language-explanation
confidence-scoring
fallback-strategy
ensemble-ai
mlops
ai-orchestration
llmops
prompt-engineering
token-efficiency
aiops
llm-observability
model-governance
open-ai-compatibility
chat-completion-api
openai-compatible
v1-chat-completions
streaming
function-calling
agentic-ai
rag-routing
enterprise-llm
startup-llm
healthcare-llm
code-assistant
creative-writing-ai
math-reasoning
factual-qna
llm-gateway
smart-proxy
model-proxy
ai-gateway
inference-optimization
gpu-saving
cost-saving
latency-optimization
real-time-inference
edge-ai
on-device-inference
embedded-llm
edge-deployment
mobile-friendly
cpu-only
no-gpu-needed
feature-extraction
Instructions to use wahidmounir/fugusashi-v1.3-Q8_0-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- HERMES
How to use wahidmounir/fugusashi-v1.3-Q8_0-GGUF with HERMES:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use wahidmounir/fugusashi-v1.3-Q8_0-GGUF 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 wahidmounir/fugusashi-v1.3-Q8_0-GGUF:Q8_0 # Run inference directly in the terminal: llama cli -hf wahidmounir/fugusashi-v1.3-Q8_0-GGUF:Q8_0
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf wahidmounir/fugusashi-v1.3-Q8_0-GGUF:Q8_0 # Run inference directly in the terminal: llama cli -hf wahidmounir/fugusashi-v1.3-Q8_0-GGUF:Q8_0
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 wahidmounir/fugusashi-v1.3-Q8_0-GGUF:Q8_0 # Run inference directly in the terminal: ./llama-cli -hf wahidmounir/fugusashi-v1.3-Q8_0-GGUF:Q8_0
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 wahidmounir/fugusashi-v1.3-Q8_0-GGUF:Q8_0 # Run inference directly in the terminal: ./build/bin/llama-cli -hf wahidmounir/fugusashi-v1.3-Q8_0-GGUF:Q8_0
Use Docker
docker model run hf.co/wahidmounir/fugusashi-v1.3-Q8_0-GGUF:Q8_0
- LM Studio
- Jan
- Ollama
How to use wahidmounir/fugusashi-v1.3-Q8_0-GGUF with Ollama:
ollama run hf.co/wahidmounir/fugusashi-v1.3-Q8_0-GGUF:Q8_0
- Unsloth Studio
How to use wahidmounir/fugusashi-v1.3-Q8_0-GGUF 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 wahidmounir/fugusashi-v1.3-Q8_0-GGUF 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 wahidmounir/fugusashi-v1.3-Q8_0-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for wahidmounir/fugusashi-v1.3-Q8_0-GGUF to start chatting
- Docker Model Runner
How to use wahidmounir/fugusashi-v1.3-Q8_0-GGUF with Docker Model Runner:
docker model run hf.co/wahidmounir/fugusashi-v1.3-Q8_0-GGUF:Q8_0
- Lemonade
How to use wahidmounir/fugusashi-v1.3-Q8_0-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull wahidmounir/fugusashi-v1.3-Q8_0-GGUF:Q8_0
Run and chat with the model
lemonade run user.fugusashi-v1.3-Q8_0-GGUF-Q8_0
List all available models
lemonade list
- Atomic Chat
Ctrl+K