Text Generation
Transformers
Safetensors
English
lfm2
linux
bash
shell
command-generation
conversational
Instructions to use thealper2/lfm2-700m-linux-command with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use thealper2/lfm2-700m-linux-command with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="thealper2/lfm2-700m-linux-command") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("thealper2/lfm2-700m-linux-command") model = AutoModelForCausalLM.from_pretrained("thealper2/lfm2-700m-linux-command", 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=256) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use thealper2/lfm2-700m-linux-command with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "thealper2/lfm2-700m-linux-command" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "thealper2/lfm2-700m-linux-command", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/thealper2/lfm2-700m-linux-command
- SGLang
How to use thealper2/lfm2-700m-linux-command 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 "thealper2/lfm2-700m-linux-command" \ --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": "thealper2/lfm2-700m-linux-command", "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 "thealper2/lfm2-700m-linux-command" \ --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": "thealper2/lfm2-700m-linux-command", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use thealper2/lfm2-700m-linux-command with Docker Model Runner:
docker model run hf.co/thealper2/lfm2-700m-linux-command
File size: 3,099 Bytes
bc6c786 | 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 | {{- bos_token -}}
{%- macro format_arg_value(arg_value) -%}
{%- if arg_value is string -%}
{{- "'" + (arg_value | replace("\\", "\\\\") | replace("'", "\\'") | replace("\n", "\\n") | replace("\r", "\\r")) + "'" -}}
{%- elif arg_value is mapping or arg_value is iterable -%}
{{- arg_value | tojson -}}
{%- else -%}
{{- arg_value | string -}}
{%- endif -%}
{%- endmacro -%}
{%- macro render_tool_calls(tool_calls) -%}
{%- set tool_calls_ns = namespace(tool_calls=[]) -%}
{%- for tool_call in tool_calls -%}
{%- set func = tool_call["function"] if "function" in tool_call else tool_call -%}
{%- set func_name = func["name"] -%}
{%- set func_args = func.get("arguments") -%}
{%- set args_ns = namespace(arg_strings=[]) -%}
{%- if func_args is mapping -%}
{%- for arg_name, arg_value in func_args.items() -%}
{%- set args_ns.arg_strings = args_ns.arg_strings + [arg_name + "=" + format_arg_value(arg_value)] -%}
{%- endfor -%}
{%- elif func_args is string and (func_args | trim) not in ["", "{}", "null"] -%}
{{- raise_exception("Tool call arguments must be a mapping, got a JSON-encoded string: parse arguments with json.loads() before applying the chat template") -}}
{%- endif -%}
{%- set tool_calls_ns.tool_calls = tool_calls_ns.tool_calls + [func_name + "(" + (args_ns.arg_strings | join(", ")) + ")"] -%}
{%- endfor -%}
{{- "<|tool_call_start|>[" + (tool_calls_ns.tool_calls | join(", ")) + "]<|tool_call_end|>" -}}
{%- endmacro -%}
{%- set system_prompt = "" -%}
{%- set ns = namespace(system_prompt="") -%}
{%- if messages[0]["role"] == "system" -%}
{%- set ns.system_prompt = messages[0]["content"] -%}
{%- set messages = messages[1:] -%}
{%- endif -%}
{%- if tools -%}
{%- set ns.system_prompt = ns.system_prompt + ("\n" if ns.system_prompt else "") + "List of tools: <|tool_list_start|>[" -%}
{%- for tool in tools -%}
{%- if tool is not string -%}
{%- set tool = tool | tojson -%}
{%- endif -%}
{%- set ns.system_prompt = ns.system_prompt + tool -%}
{%- if not loop.last -%}
{%- set ns.system_prompt = ns.system_prompt + ", " -%}
{%- endif -%}
{%- endfor -%}
{%- set ns.system_prompt = ns.system_prompt + "]<|tool_list_end|>" -%}
{%- endif -%}
{%- if ns.system_prompt -%}
{{- "<|im_start|>system\n" + ns.system_prompt + "<|im_end|>\n" -}}
{%- endif -%}
{%- for message in messages -%}
{{- "<|im_start|>" + message["role"] + "\n" -}}
{%- set content = message.get("content") -%}
{%- if content is not string -%}
{%- set content = content | tojson -%}
{%- endif -%}
{%- if message["role"] == "tool" -%}
{%- set content = "<|tool_response_start|>" + content + "<|tool_response_end|>" -%}
{%- endif -%}
{%- if message["role"] == "assistant" and message.get("tool_calls") -%}
{%- if content and content != "null" -%}
{{- content -}}
{%- endif -%}
{{- render_tool_calls(message["tool_calls"]) -}}
{{- "<|im_end|>\n" -}}
{%- else -%}
{{- content + "<|im_end|>\n" -}}
{%- endif -%}
{%- endfor -%}
{%- if add_generation_prompt -%}
{{- "<|im_start|>assistant\n" -}}
{%- endif -%} |