Transformers
Safetensors
GGUF
mixtral
Mixture of Experts
validation
test-suite
japanese
scratch-trained
Instructions to use shibatch/tinymoeja2m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shibatch/tinymoeja2m with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("shibatch/tinymoeja2m", dtype="auto") - llama-cpp-python
How to use shibatch/tinymoeja2m with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="shibatch/tinymoeja2m", filename="tinymoeja2m.BF16.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 shibatch/tinymoeja2m 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 shibatch/tinymoeja2m:Q4_K_M # Run inference directly in the terminal: llama cli -hf shibatch/tinymoeja2m:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf shibatch/tinymoeja2m:Q4_K_M # Run inference directly in the terminal: llama cli -hf shibatch/tinymoeja2m:Q4_K_M
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 shibatch/tinymoeja2m:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf shibatch/tinymoeja2m:Q4_K_M
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 shibatch/tinymoeja2m:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf shibatch/tinymoeja2m:Q4_K_M
Use Docker
docker model run hf.co/shibatch/tinymoeja2m:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use shibatch/tinymoeja2m with Ollama:
ollama run hf.co/shibatch/tinymoeja2m:Q4_K_M
- Unsloth Studio
How to use shibatch/tinymoeja2m 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 shibatch/tinymoeja2m 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 shibatch/tinymoeja2m to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for shibatch/tinymoeja2m to start chatting
- Atomic Chat new
- Docker Model Runner
How to use shibatch/tinymoeja2m with Docker Model Runner:
docker model run hf.co/shibatch/tinymoeja2m:Q4_K_M
- Lemonade
How to use shibatch/tinymoeja2m with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull shibatch/tinymoeja2m:Q4_K_M
Run and chat with the model
lemonade run user.tinymoeja2m-Q4_K_M
List all available models
lemonade list
| { | |
| "version": "1.0", | |
| "truncation": null, | |
| "padding": null, | |
| "added_tokens": [ | |
| { | |
| "id": 0, | |
| "content": "<unk>", | |
| "single_word": false, | |
| "lstrip": false, | |
| "rstrip": false, | |
| "normalized": false, | |
| "special": true | |
| }, | |
| { | |
| "id": 1, | |
| "content": "<s>", | |
| "single_word": false, | |
| "lstrip": false, | |
| "rstrip": false, | |
| "normalized": false, | |
| "special": true | |
| }, | |
| { | |
| "id": 2, | |
| "content": "</s>", | |
| "single_word": false, | |
| "lstrip": false, | |
| "rstrip": false, | |
| "normalized": false, | |
| "special": true | |
| } | |
| ], | |
| "normalizer": null, | |
| "pre_tokenizer": { | |
| "type": "Metaspace", | |
| "replacement": "▁", | |
| "prepend_scheme": "first", | |
| "split": false | |
| }, | |
| "post_processor": { | |
| "type": "TemplateProcessing", | |
| "single": [ | |
| { | |
| "Sequence": { | |
| "id": "A", | |
| "type_id": 0 | |
| } | |
| } | |
| ], | |
| "pair": [ | |
| { | |
| "Sequence": { | |
| "id": "A", | |
| "type_id": 0 | |
| } | |
| }, | |
| { | |
| "Sequence": { | |
| "id": "B", | |
| "type_id": 1 | |
| } | |
| } | |
| ], | |
| "special_tokens": {} | |
| }, | |
| "decoder": { | |
| "type": "Sequence", | |
| "decoders": [ | |
| { | |
| "type": "Replace", | |
| "pattern": { | |
| "String": "▁" | |
| }, | |
| "content": " " | |
| }, | |
| { | |
| "type": "ByteFallback" | |
| }, | |
| { | |
| "type": "Fuse" | |
| }, | |
| { | |
| "type": "Strip", | |
| "content": " ", | |
| "start": 1, | |
| "stop": 0 | |
| } | |
| ] | |
| }, | |
| "model": { | |
| "type": "BPE", | |
| "dropout": null, | |
| "unk_token": null, | |
| "continuing_subword_prefix": null, | |
| "end_of_word_suffix": null, | |
| "fuse_unk": true, | |
| "byte_fallback": true, | |
| "ignore_merges": false, | |
| "vocab": { | |
| "<unk>": 0, | |
| "<s>": 1, | |
| "</s>": 2 | |
| }, | |
| "merges": [] | |
| } | |
| } |