Instructions to use TechCarbasa/MyModels with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use TechCarbasa/MyModels with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="TechCarbasa/MyModels", filename="workspace/ComfyUI/models/WanVideo/Wan2.1-single/wan2.1-i2v-14b-480p-Q5_0.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use TechCarbasa/MyModels with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf TechCarbasa/MyModels:Q5_0 # Run inference directly in the terminal: llama-cli -hf TechCarbasa/MyModels:Q5_0
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf TechCarbasa/MyModels:Q5_0 # Run inference directly in the terminal: llama-cli -hf TechCarbasa/MyModels:Q5_0
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 TechCarbasa/MyModels:Q5_0 # Run inference directly in the terminal: ./llama-cli -hf TechCarbasa/MyModels:Q5_0
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 TechCarbasa/MyModels:Q5_0 # Run inference directly in the terminal: ./build/bin/llama-cli -hf TechCarbasa/MyModels:Q5_0
Use Docker
docker model run hf.co/TechCarbasa/MyModels:Q5_0
- LM Studio
- Jan
- Ollama
How to use TechCarbasa/MyModels with Ollama:
ollama run hf.co/TechCarbasa/MyModels:Q5_0
- Unsloth Studio
How to use TechCarbasa/MyModels 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 TechCarbasa/MyModels 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 TechCarbasa/MyModels to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for TechCarbasa/MyModels to start chatting
- Pi
How to use TechCarbasa/MyModels with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf TechCarbasa/MyModels:Q5_0
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "TechCarbasa/MyModels:Q5_0" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use TechCarbasa/MyModels with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf TechCarbasa/MyModels:Q5_0
Configure Hermes
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default TechCarbasa/MyModels:Q5_0
Run Hermes
hermes
- Docker Model Runner
How to use TechCarbasa/MyModels with Docker Model Runner:
docker model run hf.co/TechCarbasa/MyModels:Q5_0
- Lemonade
How to use TechCarbasa/MyModels with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull TechCarbasa/MyModels:Q5_0
Run and chat with the model
lemonade run user.MyModels-Q5_0
List all available models
lemonade list
File size: 1,689 Bytes
e068b0a | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 | {
"_name_or_path": "jonathandinu/face-parsing",
"architectures": [
"SegformerForSemanticSegmentation"
],
"attention_probs_dropout_prob": 0.0,
"classifier_dropout_prob": 0.1,
"decoder_hidden_size": 768,
"depths": [
3,
6,
40,
3
],
"downsampling_rates": [
1,
4,
8,
16
],
"drop_path_rate": 0.1,
"hidden_act": "gelu",
"hidden_dropout_prob": 0.0,
"hidden_sizes": [
64,
128,
320,
512
],
"id2label": {
"0": "background",
"1": "skin",
"2": "nose",
"3": "eye_g",
"4": "l_eye",
"5": "r_eye",
"6": "l_brow",
"7": "r_brow",
"8": "l_ear",
"9": "r_ear",
"10": "mouth",
"11": "u_lip",
"12": "l_lip",
"13": "hair",
"14": "hat",
"15": "ear_r",
"16": "neck_l",
"17": "neck",
"18": "cloth"
},
"image_size": 224,
"initializer_range": 0.02,
"label2id": {
"background": 0,
"skin": 1,
"nose": 2,
"eye_g": 3,
"l_eye": 4,
"r_eye": 5,
"l_brow": 6,
"r_brow": 7,
"l_ear": 8,
"r_ear": 9,
"mouth": 10,
"u_lip": 11,
"l_lip": 12,
"hair": 13,
"hat": 14,
"ear_r": 15,
"neck_l": 16,
"neck": 17,
"cloth": 18
},
"layer_norm_eps": 1e-06,
"mlp_ratios": [
4,
4,
4,
4
],
"model_type": "segformer",
"num_attention_heads": [
1,
2,
5,
8
],
"num_channels": 3,
"num_encoder_blocks": 4,
"patch_sizes": [
7,
3,
3,
3
],
"reshape_last_stage": true,
"semantic_loss_ignore_index": 255,
"sr_ratios": [
8,
4,
2,
1
],
"strides": [
4,
2,
2,
2
],
"transformers_version": "4.37.0.dev0"
}
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