Instructions to use Aliguinga01/rule_violation2 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 Aliguinga01/rule_violation2 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 Aliguinga01/rule_violation2:F16 # Run inference directly in the terminal: llama cli -hf Aliguinga01/rule_violation2:F16
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf Aliguinga01/rule_violation2:F16 # Run inference directly in the terminal: llama cli -hf Aliguinga01/rule_violation2:F16
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 Aliguinga01/rule_violation2:F16 # Run inference directly in the terminal: ./llama-cli -hf Aliguinga01/rule_violation2:F16
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 Aliguinga01/rule_violation2:F16 # Run inference directly in the terminal: ./build/bin/llama-cli -hf Aliguinga01/rule_violation2:F16
Use Docker
docker model run hf.co/Aliguinga01/rule_violation2:F16
- LM Studio
- Jan
- Ollama
How to use Aliguinga01/rule_violation2 with Ollama:
ollama run hf.co/Aliguinga01/rule_violation2:F16
- Unsloth Studio
How to use Aliguinga01/rule_violation2 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 Aliguinga01/rule_violation2 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 Aliguinga01/rule_violation2 to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Aliguinga01/rule_violation2 to start chatting
- Docker Model Runner
How to use Aliguinga01/rule_violation2 with Docker Model Runner:
docker model run hf.co/Aliguinga01/rule_violation2:F16
- Lemonade
How to use Aliguinga01/rule_violation2 with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Aliguinga01/rule_violation2:F16
Run and chat with the model
lemonade run user.rule_violation2-F16
List all available models
lemonade list
- Atomic Chat
File size: 3,534 Bytes
4d35814 | 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 | import pytest
from utils import *
# We use a F16 MOE gguf as main model, and q4_0 as draft model
server = ServerPreset.stories15m_moe()
MODEL_DRAFT_FILE_URL = "https://huggingface.co/ggml-org/models/resolve/main/tinyllamas/stories15M-q4_0.gguf"
def create_server():
global server
server = ServerPreset.stories15m_moe()
# set default values
server.model_draft = download_file(MODEL_DRAFT_FILE_URL)
server.draft_min = 4
server.draft_max = 8
server.fa = "off"
@pytest.fixture(autouse=True)
def fixture_create_server():
return create_server()
def test_with_and_without_draft():
global server
server.model_draft = None # disable draft model
server.start()
res = server.make_request("POST", "/completion", data={
"prompt": "I believe the meaning of life is",
"temperature": 0.0,
"top_k": 1,
})
assert res.status_code == 200
content_no_draft = res.body["content"]
server.stop()
# create new server with draft model
create_server()
server.start()
res = server.make_request("POST", "/completion", data={
"prompt": "I believe the meaning of life is",
"temperature": 0.0,
"top_k": 1,
})
assert res.status_code == 200
content_draft = res.body["content"]
assert content_no_draft == content_draft
def test_different_draft_min_draft_max():
global server
test_values = [
(1, 2),
(1, 4),
(4, 8),
(4, 12),
(8, 16),
]
last_content = None
for draft_min, draft_max in test_values:
server.stop()
server.draft_min = draft_min
server.draft_max = draft_max
server.start()
res = server.make_request("POST", "/completion", data={
"prompt": "I believe the meaning of life is",
"temperature": 0.0,
"top_k": 1,
})
assert res.status_code == 200
if last_content is not None:
assert last_content == res.body["content"]
last_content = res.body["content"]
def test_slot_ctx_not_exceeded():
global server
server.n_ctx = 64
server.start()
res = server.make_request("POST", "/completion", data={
"prompt": "Hello " * 56,
"temperature": 0.0,
"top_k": 1,
"speculative.p_min": 0.0,
})
assert res.status_code == 200
assert len(res.body["content"]) > 0
def test_with_ctx_shift():
global server
server.n_ctx = 64
server.enable_ctx_shift = True
server.start()
res = server.make_request("POST", "/completion", data={
"prompt": "Hello " * 56,
"temperature": 0.0,
"top_k": 1,
"n_predict": 64,
"speculative.p_min": 0.0,
})
assert res.status_code == 200
assert len(res.body["content"]) > 0
assert res.body["tokens_predicted"] == 64
assert res.body["truncated"] == True
@pytest.mark.parametrize("n_slots,n_requests", [
(1, 2),
(2, 2),
])
def test_multi_requests_parallel(n_slots: int, n_requests: int):
global server
server.n_slots = n_slots
server.start()
tasks = []
for _ in range(n_requests):
tasks.append((server.make_request, ("POST", "/completion", {
"prompt": "I believe the meaning of life is",
"temperature": 0.0,
"top_k": 1,
})))
results = parallel_function_calls(tasks)
for res in results:
assert res.status_code == 200
assert match_regex("(wise|kind|owl|answer)+", res.body["content"])
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