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Instructions to use tanya8997/openwork-understudy-0.5b 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 tanya8997/openwork-understudy-0.5b 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 tanya8997/openwork-understudy-0.5b:Q4_K_M # Run inference directly in the terminal: llama cli -hf tanya8997/openwork-understudy-0.5b:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf tanya8997/openwork-understudy-0.5b:Q4_K_M # Run inference directly in the terminal: llama cli -hf tanya8997/openwork-understudy-0.5b: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 tanya8997/openwork-understudy-0.5b:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf tanya8997/openwork-understudy-0.5b: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 tanya8997/openwork-understudy-0.5b:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf tanya8997/openwork-understudy-0.5b:Q4_K_M
Use Docker
docker model run hf.co/tanya8997/openwork-understudy-0.5b:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use tanya8997/openwork-understudy-0.5b with Ollama:
ollama run hf.co/tanya8997/openwork-understudy-0.5b:Q4_K_M
- Unsloth Studio
How to use tanya8997/openwork-understudy-0.5b 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 tanya8997/openwork-understudy-0.5b 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 tanya8997/openwork-understudy-0.5b to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for tanya8997/openwork-understudy-0.5b to start chatting
- Atomic Chat new
- Docker Model Runner
How to use tanya8997/openwork-understudy-0.5b with Docker Model Runner:
docker model run hf.co/tanya8997/openwork-understudy-0.5b:Q4_K_M
- Lemonade
How to use tanya8997/openwork-understudy-0.5b with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull tanya8997/openwork-understudy-0.5b:Q4_K_M
Run and chat with the model
lemonade run user.openwork-understudy-0.5b-Q4_K_M
List all available models
lemonade list
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| "architectures": [ | |
| "MiniCPMForCausalLM" | |
| ], | |
| "attention_bias": false, | |
| "attention_dropout": 0.0, | |
| "auto_map": { | |
| "AutoConfig": "configuration_minicpm.MiniCPMConfig", | |
| "AutoModel": "modeling_minicpm.MiniCPMModel", | |
| "AutoModelForCausalLM": "modeling_minicpm.MiniCPMForCausalLM", | |
| "AutoModelForSeq2SeqLM": "modeling_minicpm.MiniCPMForCausalLM", | |
| "AutoModelForSequenceClassification": "modeling_minicpm.MiniCPMForSequenceClassification" | |
| }, | |
| "bos_token_id": 1, | |
| "dim_model_base": 256, | |
| "dtype": "bfloat16", | |
| "eos_token_id": 73440, | |
| "hidden_act": "silu", | |
| "hidden_size": 1024, | |
| "initializer_range": 0.1, | |
| "intermediate_size": 4096, | |
| "max_position_embeddings": 32768, | |
| "model_type": "minicpm", | |
| "mup_denominator": null, | |
| "num_attention_heads": 16, | |
| "num_hidden_layers": 24, | |
| "num_key_value_heads": 2, | |
| "pad_token_id": 73440, | |
| "pretraining_tp": 1, | |
| "rms_norm_eps": 1e-05, | |
| "rope_scaling": { | |
| "long_factor": [ | |
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| ], | |
| "original_max_position_embeddings": 32768, | |
| "rope_type": "longrope", | |
| "short_factor": [ | |
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| 49.85338592529297 | |
| ] | |
| }, | |
| "rope_theta": 10000.0, | |
| "scale_depth": 1.4, | |
| "scale_emb": 12, | |
| "sparse_config": null, | |
| "transformers_version": "4.57.6", | |
| "use_cache": true, | |
| "vocab_size": 73448 | |
| } | |