Instructions to use alexgusevski/Falcon-H1R-7B-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use alexgusevski/Falcon-H1R-7B-mlx with MLX:
# Make sure mlx-lm is installed # pip install --upgrade mlx-lm # Generate text with mlx-lm from mlx_lm import load, generate model, tokenizer = load("alexgusevski/Falcon-H1R-7B-mlx") prompt = "Write a story about Einstein" messages = [{"role": "user", "content": prompt}] prompt = tokenizer.apply_chat_template( messages, add_generation_prompt=True ) text = generate(model, tokenizer, prompt=prompt, verbose=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Pi
How to use alexgusevski/Falcon-H1R-7B-mlx with Pi:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "alexgusevski/Falcon-H1R-7B-mlx"
Configure the model in Pi
# Install Pi: npm install -g @earendil-works/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "mlx-lm": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "alexgusevski/Falcon-H1R-7B-mlx" } ] } } }Run Pi
# Start Pi in your project directory: pi
- MLX LM
How to use alexgusevski/Falcon-H1R-7B-mlx with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Interactive chat REPL mlx_lm.chat --model "alexgusevski/Falcon-H1R-7B-mlx"
Run an OpenAI-compatible server
# Install MLX LM uv tool install mlx-lm # Start the server mlx_lm.server --model "alexgusevski/Falcon-H1R-7B-mlx" # Calling the OpenAI-compatible server with curl curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "alexgusevski/Falcon-H1R-7B-mlx", "messages": [ {"role": "user", "content": "Hello"} ] }' - Hermes Agent
How to use alexgusevski/Falcon-H1R-7B-mlx with Hermes Agent:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "alexgusevski/Falcon-H1R-7B-mlx"
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 alexgusevski/Falcon-H1R-7B-mlx
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use alexgusevski/Falcon-H1R-7B-mlx with OpenClaw:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "alexgusevski/Falcon-H1R-7B-mlx"
Configure OpenClaw
# Install OpenClaw: npm install -g openclaw@latest # Register the local server and set it as the default model: openclaw onboard --non-interactive --mode local \ --auth-choice custom-api-key \ --custom-base-url http://127.0.0.1:8080/v1 \ --custom-model-id "alexgusevski/Falcon-H1R-7B-mlx" \ --custom-provider-id mlx-lm \ --custom-compatibility openai \ --custom-text-input \ --accept-risk \ --skip-health
Run OpenClaw
openclaw agent --local --agent main --message "Hello from Hugging Face"
File size: 4,237 Bytes
6cf8d4b | 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 | {# --- System Prompt Handling --- #}
{%- if messages and messages[0]['role'] == 'system' %}
{% set system_msg = messages[0]['content'] %}
{%- set remaining_messages = messages[1:] %}
{%- else %}
{% set system_msg = "You are Falcon, a helpful AI assistant created by Technology Innovation Institute (TII). To answer the user's question, you first think about the reasoning process and then provide the user with the answer. The reasoning process is enclosed within <think> </think> tags, i.e., <think> reasoning process here </think> answer here." %}
{%- set remaining_messages = messages %}
{%- endif %}
{%- if tools %}
<|im_start|>system
{{ system_msg }}
# Tools
You may call one or more functions to assist with the user query. You are provided with function signatures within <tools></tools> XML tags.
<tools>
{%- for tool in tools %}
{{- "" }}
{{ tool | tojson }}
{%- endfor %}
{{- "" }}
</tools>
For each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:
<tool_call>
{"name": <function-name>, "arguments": <args-json-object>}
</tool_call>
<|im_end|>
{%- else %}
<|im_start|>system
{{ system_msg }}
<|im_end|>
{%- endif %}
{# --- Render remaining messages --- #}
{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
{%- for message in messages[::-1] %}
{%- set index = (messages|length - 1) - loop.index0 %}
{%- 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>')) %}
{%- set ns.multi_step_tool = false %}
{%- set ns.last_query_index = index %}
{%- endif %}
{%- endfor %}{%- for message in remaining_messages %}
{%- set content = message.get('content','') %}
{%- if message['role'] == 'user' %}
{{- '<|im_start|>' + message['role'] + '\n' + content + '<|im_end|>\n' }}
{%- elif message['role'] == 'assistant' %}
{{- '<|im_start|>' + message.role + '\n' }}
{%- set reasoning_content = '' %}
{%- if message.reasoning_content is string %}
{%- set reasoning_content = message.reasoning_content %}
{%- else %}
{%- if '</think>' in content %}
{%- set reasoning_content = content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
{%- set content = content.split('</think>')[-1].lstrip('\n') %}
{%- endif %}
{%- endif %}
{%- if loop.index0 > ns.last_query_index %}
{%- if loop.last or (not loop.last and reasoning_content) %}
{{- '<think>\n' + reasoning_content.strip('\n') + '\n</think>\n\n' + content.lstrip('\n') }}
{%- else %}
{{- content + '\n' }}
{%- endif %}
{%- else %}
{{- content + '\n' }}
{%- endif %}
{%- if tools and message.tool_calls %}
{%- for tool_call in message.tool_calls %}
{%- if tool_call.function is defined %}
{%- set tool_call = tool_call.function %}
{%- endif %}
{{-'<tool_call>\n' }}
{{- '{"name": "'+ tool_call.name + '", "arguments":' }}
{%- if tool_call.arguments is string -%}
{{ tool_call.arguments }}
{%- else -%}
{{ tool_call.arguments | tojson }}
{%- endif -%}
{{- '}' }}
{{- '\n</tool_call>\n' }}
{%- endfor %}
{%- endif %}
{%- if not loop.last %}
{{- '<|im_end|>' + '\n' }}
{%- else %}
{{- '<|im_end|>' }}
{%- endif %}
{%- elif message['role'] == 'tool' %}
{# Tool responses treated as user messages #}
{%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != "tool") %}
{{- '<|im_start|>user' }}
{%- endif %}
{{- '\n<tool_response>\n' + message['content'] + '\n</tool_response>' }}
{%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
{{- '<|im_end|>\n' }}
{%- endif %}
{%- endif %}
{# --- Add generation prompt after last message if requested --- #}
{%- if loop.last and add_generation_prompt %}
{{- '<|im_start|>assistant\n' }}
{%- endif %}
{%- endfor %}
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