Question Answering
Safetensors
GGUF
Turkish
English
gpt2
aquarium
aqua
biology
text-generation-inference
Instructions to use oytunistrator/AquaLLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use oytunistrator/AquaLLM with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="oytunistrator/AquaLLM", filename="aquallm.gguf", )
output = llm( "Once upon a time,", max_tokens=512, echo=True ) print(output)
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use oytunistrator/AquaLLM with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf oytunistrator/AquaLLM # Run inference directly in the terminal: llama-cli -hf oytunistrator/AquaLLM
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf oytunistrator/AquaLLM # Run inference directly in the terminal: llama-cli -hf oytunistrator/AquaLLM
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 oytunistrator/AquaLLM # Run inference directly in the terminal: ./llama-cli -hf oytunistrator/AquaLLM
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 oytunistrator/AquaLLM # Run inference directly in the terminal: ./build/bin/llama-cli -hf oytunistrator/AquaLLM
Use Docker
docker model run hf.co/oytunistrator/AquaLLM
- LM Studio
- Jan
- Ollama
How to use oytunistrator/AquaLLM with Ollama:
ollama run hf.co/oytunistrator/AquaLLM
- Unsloth Studio
How to use oytunistrator/AquaLLM 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 oytunistrator/AquaLLM 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 oytunistrator/AquaLLM to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for oytunistrator/AquaLLM to start chatting
- Docker Model Runner
How to use oytunistrator/AquaLLM with Docker Model Runner:
docker model run hf.co/oytunistrator/AquaLLM
- Lemonade
How to use oytunistrator/AquaLLM with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull oytunistrator/AquaLLM
Run and chat with the model
lemonade run user.AquaLLM-{{QUANT_TAG}}List all available models
lemonade list
| { | |
| "activation_function": "gelu_new", | |
| "architectures": [ | |
| "GPT2LMHeadModel" | |
| ], | |
| "attn_pdrop": 0.1, | |
| "bos_token_id": 50256, | |
| "embd_pdrop": 0.1, | |
| "eos_token_id": 50256, | |
| "initializer_range": 0.02, | |
| "layer_norm_epsilon": 1e-05, | |
| "model_type": "gpt2", | |
| "n_ctx": 1024, | |
| "n_embd": 768, | |
| "n_head": 12, | |
| "n_inner": null, | |
| "n_layer": 12, | |
| "n_positions": 1024, | |
| "reorder_and_upcast_attn": false, | |
| "resid_pdrop": 0.1, | |
| "scale_attn_by_inverse_layer_idx": false, | |
| "scale_attn_weights": true, | |
| "summary_activation": null, | |
| "summary_first_dropout": 0.1, | |
| "summary_proj_to_labels": true, | |
| "summary_type": "cls_index", | |
| "summary_use_proj": true, | |
| "task_specific_params": { | |
| "text-generation": { | |
| "do_sample": true, | |
| "max_length": 50 | |
| } | |
| }, | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.52.4", | |
| "use_cache": true, | |
| "vocab_size": 50257 | |
| } | |