Text Generation
Transformers
Safetensors
GGUF
English
granite
granite-4.2
formal-logic
reasoning
lora
model-merging
wise-ft
reinforcement-learning
grpo
conversational
Instructions to use webAI-Official/TwIL-LM3-Pro with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use webAI-Official/TwIL-LM3-Pro with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="webAI-Official/TwIL-LM3-Pro") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("webAI-Official/TwIL-LM3-Pro") model = AutoModelForCausalLM.from_pretrained("webAI-Official/TwIL-LM3-Pro", device_map="auto") messages = [ {"role": "user", "content": "Who are you?"}, ] inputs = tokenizer.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=40) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use webAI-Official/TwIL-LM3-Pro 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 webAI-Official/TwIL-LM3-Pro:Q4_K_M # Run inference directly in the terminal: llama cli -hf webAI-Official/TwIL-LM3-Pro:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf webAI-Official/TwIL-LM3-Pro:Q4_K_M # Run inference directly in the terminal: llama cli -hf webAI-Official/TwIL-LM3-Pro:Q4_K_M
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 webAI-Official/TwIL-LM3-Pro:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf webAI-Official/TwIL-LM3-Pro:Q4_K_M
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 webAI-Official/TwIL-LM3-Pro:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf webAI-Official/TwIL-LM3-Pro:Q4_K_M
Use Docker
docker model run hf.co/webAI-Official/TwIL-LM3-Pro:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use webAI-Official/TwIL-LM3-Pro with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "webAI-Official/TwIL-LM3-Pro" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "webAI-Official/TwIL-LM3-Pro", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/webAI-Official/TwIL-LM3-Pro:Q4_K_M
- SGLang
How to use webAI-Official/TwIL-LM3-Pro with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "webAI-Official/TwIL-LM3-Pro" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "webAI-Official/TwIL-LM3-Pro", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "webAI-Official/TwIL-LM3-Pro" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "webAI-Official/TwIL-LM3-Pro", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Ollama
How to use webAI-Official/TwIL-LM3-Pro with Ollama:
ollama run hf.co/webAI-Official/TwIL-LM3-Pro:Q4_K_M
- Unsloth Desktop
- Pi
How to use webAI-Official/TwIL-LM3-Pro with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf webAI-Official/TwIL-LM3-Pro:Q4_K_M
Configure the model in Pi
# Install Pi: npm install -g @earendil-works/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "webAI-Official/TwIL-LM3-Pro:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use webAI-Official/TwIL-LM3-Pro with Docker Model Runner:
docker model run hf.co/webAI-Official/TwIL-LM3-Pro:Q4_K_M
- Lemonade
How to use webAI-Official/TwIL-LM3-Pro with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull webAI-Official/TwIL-LM3-Pro:Q4_K_M
Run and chat with the model
lemonade run user.TwIL-LM3-Pro-Q4_K_M
List all available models
lemonade list
- Hermes Agent
How to use webAI-Official/TwIL-LM3-Pro with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf webAI-Official/TwIL-LM3-Pro:Q4_K_M
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 webAI-Official/TwIL-LM3-Pro:Q4_K_M
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use webAI-Official/TwIL-LM3-Pro with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf webAI-Official/TwIL-LM3-Pro:Q4_K_M
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 "webAI-Official/TwIL-LM3-Pro:Q4_K_M" \ --custom-provider-id llama-cpp \ --custom-compatibility openai \ --custom-text-input \ --accept-risk \ --skip-health
Run OpenClaw
openclaw agent --local --agent main --message "Hello from Hugging Face"
Download tokenizer_config.json from webAI-Official/TwIL-LM3-Pro: direct link, hf CLI and curl.
- Browser
- Download file 27 kB
-
https://huggingface.co/webAI-Official/TwIL-LM3-Pro/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://webAI-Official/TwIL-LM3-Pro/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/webAI-Official/TwIL-LM3-Pro/resolve/main/tokenizer_config.json
27 kB
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| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "100320": { | |
| "content": "<|unused_51|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "100321": { | |
| "content": "<|unused_52|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "100322": { | |
| "content": "<|unused_53|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "100323": { | |
| "content": "<|unused_54|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "100324": { | |
| "content": "<|unused_55|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "100325": { | |
| "content": "<|unused_56|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "100326": { | |
| "content": "<|unused_57|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "100327": { | |
| "content": "<|unused_58|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "100328": { | |
| "content": "<|unused_59|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "100329": { | |
| "content": "<|unused_60|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "100330": { | |
| "content": "<|unused_61|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "100331": { | |
| "content": "<|unused_62|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "100332": { | |
| "content": "<|unused_63|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "100333": { | |
| "content": "<|unused_64|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "100334": { | |
| "content": "<|unused_65|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "100335": { | |
| "content": "<|unused_66|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "100336": { | |
| "content": "<|unused_67|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "100337": { | |
| "content": "<|unused_68|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "100338": { | |
| "content": "<|unused_69|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "100339": { | |
| "content": "<|unused_70|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "100340": { | |
| "content": "<|unused_71|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "100341": { | |
| "content": "<|unused_72|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "100342": { | |
| "content": "<|unused_73|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "100343": { | |
| "content": "<|unused_74|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "100344": { | |
| "content": "<|unused_75|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "100345": { | |
| "content": "<|unused_76|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "100346": { | |
| "content": "<|unused_77|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "100347": { | |
| "content": "<|unused_78|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "100348": { | |
| "content": "<|unused_79|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "100349": { | |
| "content": "<|unused_80|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "100350": { | |
| "content": "<|unused_81|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "100351": { | |
| "content": "<|unused_82|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| } | |
| }, | |
| "chat_template": "{%- macro tool_to_json(tool) -%}\n {%- set ns_tool = namespace(first=true) -%}\n {{- '{' -}}\n {%- for k, v in tool.items() -%}\n {%- if k != 'defer_loading' and k != 'strict' -%}\n {%- if not ns_tool.first -%}{{- ', ' -}}{%- endif -%}\n {%- set ns_tool.first = false -%}\n {{- '\"' ~ k ~ '\": ' ~ (v | tojson(ensure_ascii=False)) -}}\n {%- endif -%}\n {%- endfor -%}\n {{- '}' -}}\n{%- endmacro -%}\n{%- set enable_thinking = enable_thinking if enable_thinking is defined else True %}\n{%- set low_effort = low_effort if low_effort is defined else False %}\n{%- if reasoning_effort is defined and reasoning_effort is not none %}\n {%- set low_effort = reasoning_effort == \"low\" %}\n{%- endif %}\n{%- set truncate_history_thinking = truncate_history_thinking if truncate_history_thinking is defined else True %}\n\n{%- set ns = namespace(last_user_idx = -1) %}\n{%- set loop_messages = messages %}\n{%- for m in loop_messages %}\n {%- if m[\"role\"] == \"user\" %}\n {%- set ns.last_user_idx = loop.index0 %}\n {%- endif %}\n{%- endfor %}\n\n{%- if messages[0][\"role\"] == \"system\" %}\n {%- set system_message = messages[0][\"content\"] %}\n {%- set loop_messages = messages[1:] %}\n{%- else %}\n {%- set system_message = \"\" %}\n {%- set loop_messages = messages %}\n{%- endif %}\n{%- if not tools is defined %}\n {%- set tools = [] %}\n{%- endif %}\n{# Recompute last_user_idx relative to loop_messages after handling system #}\n{%- set ns = namespace(last_user_idx = -1) %}\n{%- for m in loop_messages %}\n {%- if m[\"role\"] == \"user\" %}\n {%- set ns.last_user_idx = loop.index0 %}\n {%- endif %}\n{%- endfor %}\n{%- if system_message is defined %}\n {{- \"<|im_start|>system\\n\" + system_message }}\n{%- else %}\n {%- if tools is iterable and tools | length > 0 %}\n {{- \"<|im_start|>system\\n\" }}\n {%- endif %}\n{%- endif %}\n{%- if tools is iterable and tools | length > 0 %}\n {%- if system_message is defined and system_message | length > 0 %}\n {{- \"\\n\\n\" }}\n {%- endif %}\n {{- \"# Tools\\n\\nYou have access to the following functions:\\n\\n\" }}\n {{- \"<tools>\" }}\n {%- for tool in tools %}\n {%- if tool.function is defined %}\n {%- set tool = tool.function %}\n {%- endif %}\n {%- if tool.defer_loading is not defined or not tool.defer_loading %}\n {{- '\\n' ~ tool_to_json(tool) }}\n {%- endif %}\n {%- endfor %}\n {{- \"\\n</tools>\" }}\n\n {{- '\\n\\nIf you choose to call a function ONLY reply in the following format with NO suffix:\\n\\n<tool_call>\\n<function=example_function_name>\\n<parameter=example_parameter_1>\\nvalue_1\\n</parameter>\\n<parameter=example_parameter_2>\\nThis is the value for the second parameter\\nthat can span\\nmultiple lines\\n</parameter>\\n</function>\\n</tool_call>\\n\\n<IMPORTANT>\\nReminder:\\n- Function calls MUST follow the specified format: an inner <function=...></function> block must be nested within <tool_call></tool_call> XML tags\\n- Required parameters MUST be specified\\n- You may provide optional reasoning for your function call in natural language BEFORE the function call, but NOT after\\n- If there is no function call available, answer the question like normal with your current knowledge and do not tell the user about function calls\\n</IMPORTANT>' }}\n{%- endif %}\n\n\n{%- if system_message is defined %}\n {{- '<|im_end|>\\n' }}\n{%- else %}\n {%- if tools is iterable and tools | length > 0 %}\n {{- '<|im_end|>\\n' }}\n {%- endif %}\n{%- endif %}\n\n{%- for message in loop_messages %}\n {%- if message.role == \"assistant\" %}\n {# Add reasoning content in to content field for unified processing below. #}\n {%- if message.reasoning_content is defined and message.reasoning_content is string and message.reasoning_content | trim | length > 0 %}\n {%- set content = \"<think>\\n\" ~ message.reasoning_content ~ \"\\n</think>\\n\" ~ (message.content | default('', true)) %}\n {%- else %}\n {%- set content = message.content | default('', true) %}\n {%- if content is string -%}\n {# Allow downstream logic to to take care of broken thought, only handle coherent reasoning here. #}\n {%- if '<think>' not in content and '</think>' not in content -%}\n {%- set content = \"<think></think>\" ~ content -%}\n {%- endif -%}\n {%- else -%}\n {%- set content = content -%}\n {%- endif -%}\n {%- endif %}\n {%- if message.tool_calls is defined and message.tool_calls is iterable and message.tool_calls | length > 0 %}\n {# Assistant message has tool calls. #}\n {{- '<|im_start|>assistant\\n' }}\n {%- set include_content = not (truncate_history_thinking and loop.index0 < ns.last_user_idx) %}\n {%- if content is string and content | trim | length > 0 %}\n {%- if include_content %}\n {{- (content | trim) ~ '\\n' -}}\n {%- else %}\n {%- set c = (content | string) %}\n {%- if '</think>' in c %}\n {# Keep only content after the last closing think. Also generation prompt causes this. #}\n {%- set c = c.split('</think>')[-1] %}\n {%- elif '<think>' in c %}\n {# If <think> was opened but never closed, drop the trailing think segment #}\n {%- set c = c.split('<think>')[0] %}\n {%- endif %}\n {%- set c = \"<think></think>\" ~ c | trim %}\n {%- if c | length > 0 %}\n {{- c ~ '\\n' -}}\n {%- endif %}\n {%- endif %}\n {%- else %}\n {{- \"<think></think>\" -}}\n {%- endif %}\n {%- for tool_call in message.tool_calls %}\n {%- if tool_call.function is defined %}\n {%- set tool_call = tool_call.function %}\n {%- endif %}\n {{- '<tool_call>\\n<function=' ~ tool_call.name ~ '>\\n' -}}\n {%- if tool_call.arguments is defined %}\n {%- for args_name, args_value in tool_call.arguments|items %}\n {{- '<parameter=' ~ args_name ~ '>\\n' -}}\n {%- set args_value = args_value | tojson | safe if args_value is mapping or (args_value is sequence and args_value is not string) else args_value | string %}\n {{- args_value ~ '\\n</parameter>\\n' -}}\n {%- endfor %}\n {%- endif %}\n {{- '</function>\\n</tool_call>\\n' -}}\n {%- endfor %}\n {{- '<|im_end|>\\n' }}\n {%- else %}\n {# Assistant message doesn't have tool calls. #}\n {%- if not (truncate_history_thinking and loop.index0 < ns.last_user_idx) %}\n {{- '<|im_start|>assistant\\n' ~ (content | default('', true) | string | trim) ~ '<|im_end|>\\n' }}\n {%- else %}\n {%- set c = (content | default('', true) | string) %}\n {%- if '<think>' in c and '</think>' in c %}\n {%- set c = \"<think></think>\" ~ c.split('</think>')[-1] %}\n {%- endif %}\n {%- set c = c | trim %}\n {%- if c | length > 0 %}\n {{- '<|im_start|>assistant\\n' ~ c ~ '<|im_end|>\\n' }}\n {%- else %}\n {{- '<|im_start|>assistant\\n<|im_end|>\\n' }}\n {%- endif %}\n {%- endif %}\n {%- endif %}\n {%- elif message.role == \"user\" or message.role == \"system\" %}\n {{- '<|im_start|>' + message.role + '\\n' }}\n {%- set content = message.content | string %}\n {%- if message.role == \"user\" and loop.index0 == ns.last_user_idx and low_effort %}\n {{- content + '\\n\\n{reasoning effort: low}' }}\n {%- else %}\n {{- content }}\n {%- endif %}\n {{- '<|im_end|>\\n' }}\n {%- elif message.role == \"tool\" %}\n {%- if loop.previtem and loop.previtem.role != \"tool\" %}\n {{- '<|im_start|>user\\n' }}\n {%- endif %}\n {{- '<tool_response>\\n' }}\n {{- message.content }}\n {{- '\\n</tool_response>\\n' }}\n {%- if not loop.last and loop.nextitem.role != \"tool\" %}\n {{- '<|im_end|>\\n' }}\n {%- elif loop.last %}\n {{- '<|im_end|>\\n' }}\n {%- endif %}\n {%- else %}\n {{- '<|im_start|>' + message.role + '\\n' + message.content + '<|im_end|>\\n' }}\n {%- endif %}\n{%- endfor %}\n\n{%- if add_generation_prompt %}\n {%- if enable_thinking %}\n {{- '<|im_start|>assistant\\n<think>\\n' }}\n {%- else %}\n {{- '<|im_start|>assistant\\n<think></think>' }}\n {%- endif %}\n{%- endif %}\n" | |
| } | |