Instructions to use TroyDoesAI/Agent-Flow-Phone_Demo_3GB_RAM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use TroyDoesAI/Agent-Flow-Phone_Demo_3GB_RAM with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="TroyDoesAI/Agent-Flow-Phone_Demo_3GB_RAM", filename="AgentFlow-3B-Q2_K.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 TroyDoesAI/Agent-Flow-Phone_Demo_3GB_RAM 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 TroyDoesAI/Agent-Flow-Phone_Demo_3GB_RAM:Q2_K # Run inference directly in the terminal: llama cli -hf TroyDoesAI/Agent-Flow-Phone_Demo_3GB_RAM:Q2_K
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf TroyDoesAI/Agent-Flow-Phone_Demo_3GB_RAM:Q2_K # Run inference directly in the terminal: llama cli -hf TroyDoesAI/Agent-Flow-Phone_Demo_3GB_RAM:Q2_K
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 TroyDoesAI/Agent-Flow-Phone_Demo_3GB_RAM:Q2_K # Run inference directly in the terminal: ./llama-cli -hf TroyDoesAI/Agent-Flow-Phone_Demo_3GB_RAM:Q2_K
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 TroyDoesAI/Agent-Flow-Phone_Demo_3GB_RAM:Q2_K # Run inference directly in the terminal: ./build/bin/llama-cli -hf TroyDoesAI/Agent-Flow-Phone_Demo_3GB_RAM:Q2_K
Use Docker
docker model run hf.co/TroyDoesAI/Agent-Flow-Phone_Demo_3GB_RAM:Q2_K
- LM Studio
- Jan
- Ollama
How to use TroyDoesAI/Agent-Flow-Phone_Demo_3GB_RAM with Ollama:
ollama run hf.co/TroyDoesAI/Agent-Flow-Phone_Demo_3GB_RAM:Q2_K
- Unsloth Studio
How to use TroyDoesAI/Agent-Flow-Phone_Demo_3GB_RAM 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 TroyDoesAI/Agent-Flow-Phone_Demo_3GB_RAM 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 TroyDoesAI/Agent-Flow-Phone_Demo_3GB_RAM to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for TroyDoesAI/Agent-Flow-Phone_Demo_3GB_RAM to start chatting
- Atomic Chat new
- Docker Model Runner
How to use TroyDoesAI/Agent-Flow-Phone_Demo_3GB_RAM with Docker Model Runner:
docker model run hf.co/TroyDoesAI/Agent-Flow-Phone_Demo_3GB_RAM:Q2_K
- Lemonade
How to use TroyDoesAI/Agent-Flow-Phone_Demo_3GB_RAM with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull TroyDoesAI/Agent-Flow-Phone_Demo_3GB_RAM:Q2_K
Run and chat with the model
lemonade run user.Agent-Flow-Phone_Demo_3GB_RAM-Q2_K
List all available models
lemonade list
File size: 2,198 Bytes
4222dd5 | 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 | FROM ./AgentFlow-3B.gguf
# set the temperature to 1 [higher is more creative, lower is more coherent]
PARAMETER temperature 0.644224422442
PARAMETER num_ctx 4096
# PARAMETER num_gpu 42
# PARAMETER num_thread 2
PARAMETER stop "</s>"
PARAMETER stop "<s>"
PARAMETER stop "<br/>"
PARAMETER stop "<br>"
PARAMETER stop "<|im_start|>"
PARAMETER stop "<|user|>"
PARAMETER stop "<|end|>"
PARAMETER stop "<|im_end|>"
PARAMETER stop "<|`end `|>"
PARAMETER stop "<|` end `|>"
PARAMETER stop "<|` end`|>"
PARAMETER stop "<|`---`|>"
PARAMETER stop "<|endoftext|>"
PARAMETER stop "\n\n\n"
PARAMETER stop "BEGININPUT"
PARAMETER stop "ENDINPUT"
PARAMETER stop "BEGINCONTEXT"
PARAMETER stop "ENDCONTEXT"
PARAMETER stop "BEGININSTRUCTION"
PARAMETER stop "ENDINSTRUCTION"
# PARAMETER repeat_penalty 1.6
# PARAMETER num_predict -2
PARAMETER stop "<|start_header_id|>"
PARAMETER stop "<|end_header_id|>"
PARAMETER stop "<|eot_id|>"
PARAMETER stop "<|reserved_special_token"
PARAMETER stop "<|system|>"
PARAMETER stop " \`\`\` "
# # set the system prompt
# TEMPLATE """
# <|im_start|> {{ if .System }}{{ .System }}{{ end }}{{ if .Prompt }} {{ .Prompt }} {{ end }}
# <|im_start|> {{ if .System }}{{ .System }}{{ end }} {{ .Response }} <|im_end|>
# """
# set the system prompt
# TEMPLATE """
# {{ if .System }}<|system|>
# {{ .System }}<|end|>
# {{ end }}{{ if .Prompt }}<|user|>
# {{ .Prompt }}<|end|>
# {{ end }}<|assistant|>
# {{ .Response }}<|end|>
# """
# TEMPLATE """
# BEGININPUT
# BEGINCONTEXT
# ENDCONTEXT
# {{ if .System }}<|system|>:{{ .System }}{{ end }}
# ENDINPUT
# BEGININSTRUCTION
# {{ if .Prompt }}{{ .Prompt }}{{ end }}
# ENDINSTRUCTION
# ### Contextual Response
# {{ .Response }}
# """
# TEMPLATE """
# Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.
# {{ if .System }}### Instruction:
# {{ .System }}{{ end }}
# {{ if .Prompt }}### Input:
# {{ .Prompt }}{{ end }}
# ### Response:
# """
TEMPLATE """
{{ if .Prompt }}{{ .Prompt }}{{ end }}
<|flow|>
```mermaid
{{ .Response }}
```
""" |