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lfm3
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llama.cpp
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Instructions to use HelioAI/LFM3-1.7B-inference-modules-experiments with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use HelioAI/LFM3-1.7B-inference-modules-experiments 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 HelioAI/LFM3-1.7B-inference-modules-experiments:Q5_K_M # Run inference directly in the terminal: llama cli -hf HelioAI/LFM3-1.7B-inference-modules-experiments:Q5_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf HelioAI/LFM3-1.7B-inference-modules-experiments:Q5_K_M # Run inference directly in the terminal: llama cli -hf HelioAI/LFM3-1.7B-inference-modules-experiments:Q5_K_M
Build from source code
git clone https://github.com/ggml-org/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-app # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama serve -hf HelioAI/LFM3-1.7B-inference-modules-experiments:Q5_K_M # Run inference directly in the terminal: ./build/bin/llama cli -hf HelioAI/LFM3-1.7B-inference-modules-experiments:Q5_K_M
Use Docker
docker model run hf.co/HelioAI/LFM3-1.7B-inference-modules-experiments:Q5_K_M
- Llama new
- LM Studio
- Jan
- Ollama
How to use HelioAI/LFM3-1.7B-inference-modules-experiments with Ollama:
ollama run hf.co/HelioAI/LFM3-1.7B-inference-modules-experiments:Q5_K_M
- Unsloth Desktop
- Pi
How to use HelioAI/LFM3-1.7B-inference-modules-experiments with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf HelioAI/LFM3-1.7B-inference-modules-experiments:Q5_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": "HelioAI/LFM3-1.7B-inference-modules-experiments:Q5_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use HelioAI/LFM3-1.7B-inference-modules-experiments with Docker Model Runner:
docker model run hf.co/HelioAI/LFM3-1.7B-inference-modules-experiments:Q5_K_M
- Lemonade
How to use HelioAI/LFM3-1.7B-inference-modules-experiments with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull HelioAI/LFM3-1.7B-inference-modules-experiments:Q5_K_M
Run and chat with the model
lemonade run user.LFM3-1.7B-inference-modules-experiments-Q5_K_M
List all available models
lemonade list
- Hermes Agent
How to use HelioAI/LFM3-1.7B-inference-modules-experiments with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf HelioAI/LFM3-1.7B-inference-modules-experiments:Q5_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 HelioAI/LFM3-1.7B-inference-modules-experiments:Q5_K_M
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use HelioAI/LFM3-1.7B-inference-modules-experiments with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf HelioAI/LFM3-1.7B-inference-modules-experiments:Q5_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 "HelioAI/LFM3-1.7B-inference-modules-experiments:Q5_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"
File size: 6,064 Bytes
cd61333 | 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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 | """Public tests a programmer can see in the task statement itself (never the hidden grading tests):
code_io -> Input/Output example pairs of the statement (Codeforces / AtCoder / "Sample Input" styles)
humaneval -> doctest lines (>>> call / expected value) of the docstring
mbpp -> the assert lines quoted in the prompt
run_public(task, code, prompt) -> (n_pass, n_total, first_failure_text)"""
import os
import re
import subprocess
import sandbox # noqa: E402 (same folder)
import sys
import tempfile
TMP = os.path.join(tempfile.gettempdir(), "lfm3_pub")
os.makedirs(TMP, exist_ok=True)
_HDR_IN = re.compile(r"^\s*(?:-+\s*)?(?:sample|example)?\s*input\s*(?:\d+|#\d+)?\s*:?\s*(?:-+)?\s*$", re.I)
_HDR_OUT = re.compile(r"^\s*(?:-+\s*)?(?:sample|example)?\s*output\s*(?:\d+|#\d+)?\s*:?\s*(?:-+)?\s*$", re.I)
_STOP = re.compile(r"^\s*(?:-{3,}.*|note:?|notes:?|explanation:?.*|constraints:?|write a python 3 program.*)\s*$", re.I)
_EX_HDR = re.compile(r"^\s*-*\s*(?:examples?|samples?|sample tests?)\s*\d*\s*:?\s*-*\s*$", re.I)
def _prose(text):
return len(re.findall(r"[A-Za-z]{3,}", text)) >= 12
def io_examples(prompt):
"""Example pairs after the statement's Example(s) header (format sections named Input/Output are skipped)."""
lines = prompt.replace("\r", "").split("\n")
pairs = []
i = next((k + 1 for k, l in enumerate(lines) if _EX_HDR.match(l)), 0)
while i < len(lines):
if _HDR_IN.match(lines[i]) and not re.match(r"^\s*-+\s*input\s*-+\s*$", lines[i], re.I):
j = i + 1
inp = []
while j < len(lines) and not _HDR_OUT.match(lines[j]):
if _HDR_IN.match(lines[j]) or _STOP.match(lines[j]):
break
inp.append(lines[j])
j += 1
if j < len(lines) and _HDR_OUT.match(lines[j]):
k = j + 1
out = []
while k < len(lines) and not _HDR_IN.match(lines[k]) and not _STOP.match(lines[k]):
out.append(lines[k])
k += 1
for b in range(1, len(out)): # an explanation paragraph after the expected output is not output
if not out[b].strip() and len(re.findall(r"[A-Za-z]{3,}", " ".join(out[b + 1:b + 4]))) >= 4:
out = out[:b]
break
inp_s, out_s = "\n".join(inp).strip("\n"), "\n".join(out).strip()
if inp_s.strip() and out_s and not _prose(inp_s):
pairs.append((inp_s + "\n", out_s))
i = k
continue
i += 1
return pairs
def doctests(prompt):
tests, lines = [], prompt.split("\n")
for i, l in enumerate(lines):
s = l.strip()
if s.startswith(">>>") and i + 1 < len(lines):
exp = lines[i + 1].strip()
if exp and not exp.startswith(">>>") and not exp.startswith('"""'):
tests.append((s[3:].strip(), exp))
return tests
def asserts(prompt):
return [l.strip() for l in prompt.split("\n") if l.strip().startswith("assert ")]
def _run(src, stdin="", timeout=6):
fd, path = tempfile.mkstemp(suffix=".py", dir=TMP)
with os.fdopen(fd, "w", encoding="utf-8") as f:
f.write(src)
try:
r = sandbox.run([sys.executable, "-I", path], input=stdin.encode(), capture_output=True, timeout=timeout,
cwd=TMP, creationflags=getattr(subprocess, "CREATE_NO_WINDOW", 0))
return r.returncode, r.stdout.decode(errors="replace"), r.stderr.decode(errors="replace")
except subprocess.TimeoutExpired:
return -1, "", "TimeoutError: time limit exceeded (6 s)"
finally:
try:
os.remove(path)
except OSError:
pass
def _same(got, exp):
a, b = got.split(), exp.split()
if len(a) != len(b):
return False
for x, y in zip(a, b):
if x != y:
try:
if abs(float(x) - float(y)) > 1e-6 * max(1.0, abs(float(y))):
return False
except ValueError:
return False
return True
def _tail(err, n=6):
return "\n".join(err.strip().splitlines()[-n:])
def run_public(task, code, prompt, item=None):
"""Returns (passed, total, failure description or None)."""
if task == "lcb":
from lcb_tests import run_lcb
return run_lcb(code, item, item["public"])
if task == "code_io":
tests = io_examples(prompt)
fails = None
ok = 0
for k, (inp, out) in enumerate(tests):
rc, so, se = _run(code, inp)
if rc == 0 and _same(so, out):
ok += 1
elif fails is None:
got = so.strip()[:600] if rc == 0 else (so.strip()[:300] + "\n" + _tail(se)).strip()
fails = f"Example {k + 1}\nInput:\n{inp.strip()[:800]}\nExpected output:\n{out[:600]}\n" \
f"Your program's output:\n{got or '(nothing)'}"
return ok, len(tests), fails
if task == "humaneval":
tests = doctests(prompt)
checks = [f"_r = {call}\n_e = {exp}\nprint('PASS' if _r == _e else 'FAIL ' + repr(_r))" for call, exp in tests]
elif task == "mbpp":
tests = asserts(prompt)
checks = [f"try:\n {a}\n print('PASS')\nexcept AssertionError:\n print('FAIL')" for a in tests]
else:
return 0, 0, None
ok, fails = 0, None
for k, (t, chk) in enumerate(zip(tests, checks)):
rc, so, se = _run(code + "\n\n" + chk)
if rc == 0 and so.strip().endswith("PASS"):
ok += 1
elif fails is None:
shown = t if isinstance(t, str) else f">>> {t[0]}\nexpected: {t[1]}"
res = so.strip().splitlines()[-1] if rc == 0 and so.strip() else _tail(se)
fails = f"Test:\n{shown}\nResult: {res}"
return ok, len(tests), fails
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