Instructions to use TheK0tYaRa/minicoder-lua-bf16 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 TheK0tYaRa/minicoder-lua-bf16 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 TheK0tYaRa/minicoder-lua-bf16:BF16 # Run inference directly in the terminal: llama cli -hf TheK0tYaRa/minicoder-lua-bf16:BF16
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf TheK0tYaRa/minicoder-lua-bf16:BF16 # Run inference directly in the terminal: llama cli -hf TheK0tYaRa/minicoder-lua-bf16: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 TheK0tYaRa/minicoder-lua-bf16:BF16 # Run inference directly in the terminal: ./llama-cli -hf TheK0tYaRa/minicoder-lua-bf16: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 TheK0tYaRa/minicoder-lua-bf16:BF16 # Run inference directly in the terminal: ./build/bin/llama-cli -hf TheK0tYaRa/minicoder-lua-bf16:BF16
Use Docker
docker model run hf.co/TheK0tYaRa/minicoder-lua-bf16:BF16
- LM Studio
- Jan
- Ollama
How to use TheK0tYaRa/minicoder-lua-bf16 with Ollama:
ollama run hf.co/TheK0tYaRa/minicoder-lua-bf16:BF16
- Unsloth Studio
How to use TheK0tYaRa/minicoder-lua-bf16 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 TheK0tYaRa/minicoder-lua-bf16 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 TheK0tYaRa/minicoder-lua-bf16 to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for TheK0tYaRa/minicoder-lua-bf16 to start chatting
- Docker Model Runner
How to use TheK0tYaRa/minicoder-lua-bf16 with Docker Model Runner:
docker model run hf.co/TheK0tYaRa/minicoder-lua-bf16:BF16
- Lemonade
How to use TheK0tYaRa/minicoder-lua-bf16 with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull TheK0tYaRa/minicoder-lua-bf16:BF16
Run and chat with the model
lemonade run user.minicoder-lua-bf16-BF16
List all available models
lemonade list
- Atomic Chat
Commit ·
c36e397
0
Parent(s):
Duplicate from cassanof/minicoder-lua
Browse filesCo-authored-by: Federico Cassano <cassanof@users.noreply.huggingface.co>
- .gitattributes +35 -0
- config.json +39 -0
- generation_config.json +6 -0
- merges.txt +0 -0
- pytorch_model.bin +3 -0
- special_tokens_map.json +26 -0
- tokenizer.json +0 -0
- tokenizer_config.json +31 -0
- vocab.json +0 -0
.gitattributes
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config.json
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{
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"_name_or_path": "./model_femtostarcoder_lua/checkpoint-5798",
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"activation_function": "gelu",
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"GPTBigCodeForCausalLM"
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],
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"n_inner": 768,
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"n_positions": 512,
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"summary_type": "cls_index",
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"torch_dtype": "float32",
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"transformers_version": "4.31.0",
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"use_cache": false,
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"validate_runner_input": true,
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"vocab_size": 49152
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}
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generation_config.json
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{
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"_from_model_config": true,
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"bos_token_id": 0,
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"eos_token_id": 0,
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"transformers_version": "4.31.0"
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}
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merges.txt
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:550c3e31496e8a03e638cbb598c500394548610bdee8269835dcfdf60ddb8677
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size 98514069
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special_tokens_map.json
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{
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"eos_token": "<|endoftext|>",
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"unk_token": "<|endoftext|>"
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}
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tokenizer.json
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tokenizer_config.json
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"bos_token": "<|endoftext|>",
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"clean_up_tokenization_spaces": true,
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"eos_token": "<|endoftext|>",
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"unk_token": "<|endoftext|>",
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}
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vocab.json
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