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
Upload /workspace/ComfyUI/models/face_parsing/config.json with huggingface_hub
Browse files
workspace/ComfyUI/models/face_parsing/config.json
ADDED
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| 1 |
+
{
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| 2 |
+
"_name_or_path": "jonathandinu/face-parsing",
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| 3 |
+
"architectures": [
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| 4 |
+
"SegformerForSemanticSegmentation"
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| 5 |
+
],
|
| 6 |
+
"attention_probs_dropout_prob": 0.0,
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| 7 |
+
"classifier_dropout_prob": 0.1,
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| 8 |
+
"decoder_hidden_size": 768,
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| 9 |
+
"depths": [
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| 10 |
+
3,
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| 11 |
+
6,
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| 12 |
+
40,
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| 13 |
+
3
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| 14 |
+
],
|
| 15 |
+
"downsampling_rates": [
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| 16 |
+
1,
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| 17 |
+
4,
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| 18 |
+
8,
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| 19 |
+
16
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| 20 |
+
],
|
| 21 |
+
"drop_path_rate": 0.1,
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| 22 |
+
"hidden_act": "gelu",
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| 23 |
+
"hidden_dropout_prob": 0.0,
|
| 24 |
+
"hidden_sizes": [
|
| 25 |
+
64,
|
| 26 |
+
128,
|
| 27 |
+
320,
|
| 28 |
+
512
|
| 29 |
+
],
|
| 30 |
+
"id2label": {
|
| 31 |
+
"0": "background",
|
| 32 |
+
"1": "skin",
|
| 33 |
+
"2": "nose",
|
| 34 |
+
"3": "eye_g",
|
| 35 |
+
"4": "l_eye",
|
| 36 |
+
"5": "r_eye",
|
| 37 |
+
"6": "l_brow",
|
| 38 |
+
"7": "r_brow",
|
| 39 |
+
"8": "l_ear",
|
| 40 |
+
"9": "r_ear",
|
| 41 |
+
"10": "mouth",
|
| 42 |
+
"11": "u_lip",
|
| 43 |
+
"12": "l_lip",
|
| 44 |
+
"13": "hair",
|
| 45 |
+
"14": "hat",
|
| 46 |
+
"15": "ear_r",
|
| 47 |
+
"16": "neck_l",
|
| 48 |
+
"17": "neck",
|
| 49 |
+
"18": "cloth"
|
| 50 |
+
},
|
| 51 |
+
"image_size": 224,
|
| 52 |
+
"initializer_range": 0.02,
|
| 53 |
+
"label2id": {
|
| 54 |
+
"background": 0,
|
| 55 |
+
"skin": 1,
|
| 56 |
+
"nose": 2,
|
| 57 |
+
"eye_g": 3,
|
| 58 |
+
"l_eye": 4,
|
| 59 |
+
"r_eye": 5,
|
| 60 |
+
"l_brow": 6,
|
| 61 |
+
"r_brow": 7,
|
| 62 |
+
"l_ear": 8,
|
| 63 |
+
"r_ear": 9,
|
| 64 |
+
"mouth": 10,
|
| 65 |
+
"u_lip": 11,
|
| 66 |
+
"l_lip": 12,
|
| 67 |
+
"hair": 13,
|
| 68 |
+
"hat": 14,
|
| 69 |
+
"ear_r": 15,
|
| 70 |
+
"neck_l": 16,
|
| 71 |
+
"neck": 17,
|
| 72 |
+
"cloth": 18
|
| 73 |
+
},
|
| 74 |
+
"layer_norm_eps": 1e-06,
|
| 75 |
+
"mlp_ratios": [
|
| 76 |
+
4,
|
| 77 |
+
4,
|
| 78 |
+
4,
|
| 79 |
+
4
|
| 80 |
+
],
|
| 81 |
+
"model_type": "segformer",
|
| 82 |
+
"num_attention_heads": [
|
| 83 |
+
1,
|
| 84 |
+
2,
|
| 85 |
+
5,
|
| 86 |
+
8
|
| 87 |
+
],
|
| 88 |
+
"num_channels": 3,
|
| 89 |
+
"num_encoder_blocks": 4,
|
| 90 |
+
"patch_sizes": [
|
| 91 |
+
7,
|
| 92 |
+
3,
|
| 93 |
+
3,
|
| 94 |
+
3
|
| 95 |
+
],
|
| 96 |
+
"reshape_last_stage": true,
|
| 97 |
+
"semantic_loss_ignore_index": 255,
|
| 98 |
+
"sr_ratios": [
|
| 99 |
+
8,
|
| 100 |
+
4,
|
| 101 |
+
2,
|
| 102 |
+
1
|
| 103 |
+
],
|
| 104 |
+
"strides": [
|
| 105 |
+
4,
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| 106 |
+
2,
|
| 107 |
+
2,
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| 108 |
+
2
|
| 109 |
+
],
|
| 110 |
+
"transformers_version": "4.37.0.dev0"
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| 111 |
+
}
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