Text Generation
GGUF
Safetensors
English
daedalus
cpu-inference
hybrid
conv-attention
conversational
Instructions to use Unseen1980/daedalus-checkpoints with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use Unseen1980/daedalus-checkpoints 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 Unseen1980/daedalus-checkpoints:F16 # Run inference directly in the terminal: llama cli -hf Unseen1980/daedalus-checkpoints:F16
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf Unseen1980/daedalus-checkpoints:F16 # Run inference directly in the terminal: llama cli -hf Unseen1980/daedalus-checkpoints:F16
Build from source code
git clone https://github.com/ggml-org/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-app # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama serve -hf Unseen1980/daedalus-checkpoints:F16 # Run inference directly in the terminal: ./build/bin/llama cli -hf Unseen1980/daedalus-checkpoints:F16
Use Docker
docker model run hf.co/Unseen1980/daedalus-checkpoints:F16
- Llama new
- LM Studio
- Jan
- vLLM
How to use Unseen1980/daedalus-checkpoints with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Unseen1980/daedalus-checkpoints" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Unseen1980/daedalus-checkpoints", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/Unseen1980/daedalus-checkpoints:F16
- Ollama
How to use Unseen1980/daedalus-checkpoints with Ollama:
ollama run hf.co/Unseen1980/daedalus-checkpoints:F16
- Unsloth Desktop
- Docker Model Runner
How to use Unseen1980/daedalus-checkpoints with Docker Model Runner:
docker model run hf.co/Unseen1980/daedalus-checkpoints:F16
- Lemonade
How to use Unseen1980/daedalus-checkpoints with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Unseen1980/daedalus-checkpoints:F16
Run and chat with the model
lemonade run user.daedalus-checkpoints-F16
List all available models
lemonade list
- Atomic Chat
Download hf/instruct/tokenizer_config.json from Unseen1980/daedalus-checkpoints: direct link, hf CLI and curl.
- Browser
- Download file 764 Bytes
-
https://huggingface.co/Unseen1980/daedalus-checkpoints/resolve/main/hf/instruct/tokenizer_config.json
- Command line
-
hf download hf://Unseen1980/daedalus-checkpoints/hf/instruct/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/Unseen1980/daedalus-checkpoints/resolve/main/hf/instruct/tokenizer_config.json
764 Bytes
| { | |
| "add_prefix_space": false, | |
| "backend": "tokenizers", | |
| "bos_token": "<|endoftext|>", | |
| "clean_up_tokenization_spaces": false, | |
| "eos_token": "<|endoftext|>", | |
| "errors": "replace", | |
| "extra_special_tokens": [ | |
| "<|endoftext|>", | |
| "<|im_start|>", | |
| "<|im_end|>", | |
| "<repo_name>", | |
| "<reponame>", | |
| "<file_sep>", | |
| "<filename>", | |
| "<gh_stars>", | |
| "<issue_start>", | |
| "<issue_comment>", | |
| "<issue_closed>", | |
| "<jupyter_start>", | |
| "<jupyter_text>", | |
| "<jupyter_code>", | |
| "<jupyter_output>", | |
| "<jupyter_script>", | |
| "<empty_output>" | |
| ], | |
| "is_local": false, | |
| "local_files_only": false, | |
| "model_max_length": 8192, | |
| "pad_token": null, | |
| "tokenizer_class": "GPT2Tokenizer", | |
| "unk_token": "<|endoftext|>", | |
| "vocab_size": 49152 | |
| } | |