Instructions to use dcostenco/prism-coder-14b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use dcostenco/prism-coder-14b with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="dcostenco/prism-coder-14b", filename="prism-aac-14b-q4km.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 dcostenco/prism-coder-14b with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf dcostenco/prism-coder-14b # Run inference directly in the terminal: llama-cli -hf dcostenco/prism-coder-14b
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf dcostenco/prism-coder-14b # Run inference directly in the terminal: llama-cli -hf dcostenco/prism-coder-14b
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 dcostenco/prism-coder-14b # Run inference directly in the terminal: ./llama-cli -hf dcostenco/prism-coder-14b
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 dcostenco/prism-coder-14b # Run inference directly in the terminal: ./build/bin/llama-cli -hf dcostenco/prism-coder-14b
Use Docker
docker model run hf.co/dcostenco/prism-coder-14b
- LM Studio
- Jan
- Ollama
How to use dcostenco/prism-coder-14b with Ollama:
ollama run hf.co/dcostenco/prism-coder-14b
- Unsloth Studio
How to use dcostenco/prism-coder-14b 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 dcostenco/prism-coder-14b 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 dcostenco/prism-coder-14b to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for dcostenco/prism-coder-14b to start chatting
- Pi
How to use dcostenco/prism-coder-14b with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf dcostenco/prism-coder-14b
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": "dcostenco/prism-coder-14b" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use dcostenco/prism-coder-14b with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf dcostenco/prism-coder-14b
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 dcostenco/prism-coder-14b
Run Hermes
hermes
- Docker Model Runner
How to use dcostenco/prism-coder-14b with Docker Model Runner:
docker model run hf.co/dcostenco/prism-coder-14b
- Lemonade
How to use dcostenco/prism-coder-14b with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull dcostenco/prism-coder-14b
Run and chat with the model
lemonade run user.prism-coder-14b-{{QUANT_TAG}}List all available models
lemonade list
Remove old file: chat_template.jinja
Browse files- chat_template.jinja +0 -89
chat_template.jinja
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{%- if tools %}
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{{- '<|im_start|>system\n' }}
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{%- if messages[0].role == 'system' %}
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{{- messages[0].content + '\n\n' }}
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{%- endif %}
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{{- "# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
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{%- for tool in tools %}
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{{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
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{%- else %}
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{%- if messages[0].role == 'system' %}
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{{- '<|im_start|>system\n' + messages[0].content + '<|im_end|>\n' }}
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{%- endif %}
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{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
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{%- if ns.multi_step_tool and message.role == "user" and message.content is string and not(message.content.startswith('<tool_response>') and message.content.endswith('</tool_response>')) %}
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{%- if (message.role == "user") or (message.role == "system" and not loop.first) %}
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{{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }}
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{%- set reasoning_content = content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
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{%- if loop.last or (not loop.last and reasoning_content) %}
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{{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content.strip('\n') + '\n</think>\n\n' + content.lstrip('\n') }}
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{{- '<|im_start|>' + message.role + '\n' + content }}
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{{- '<tool_call>\n{"name": "' }}
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{{- '<|im_end|>\n' }}
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{%- if loop.first or (messages[loop.index0 - 1].role != "tool") %}
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{{- '\n<tool_response>\n' }}
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{%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
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