Instructions to use Floobin/TSwifty-SN6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Floobin/TSwifty-SN6 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Floobin/TSwifty-SN6") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Floobin/TSwifty-SN6") model = AutoModelForCausalLM.from_pretrained("Floobin/TSwifty-SN6", 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
- vLLM
How to use Floobin/TSwifty-SN6 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Floobin/TSwifty-SN6" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Floobin/TSwifty-SN6", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/Floobin/TSwifty-SN6
- SGLang
How to use Floobin/TSwifty-SN6 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 "Floobin/TSwifty-SN6" \ --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": "Floobin/TSwifty-SN6", "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 "Floobin/TSwifty-SN6" \ --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": "Floobin/TSwifty-SN6", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use Floobin/TSwifty-SN6 with Docker Model Runner:
docker model run hf.co/Floobin/TSwifty-SN6
File size: 5,133 Bytes
0a594a8 | 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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 | """Module for parsing and testing package version predicate strings.
"""
import re
import distutils.version
import operator
re_validPackage = re.compile(r"(?i)^\s*([a-z_]\w*(?:\.[a-z_]\w*)*)(.*)",
re.ASCII)
# (package) (rest)
re_paren = re.compile(r"^\s*\((.*)\)\s*$") # (list) inside of parentheses
re_splitComparison = re.compile(r"^\s*(<=|>=|<|>|!=|==)\s*([^\s,]+)\s*$")
# (comp) (version)
def splitUp(pred):
"""Parse a single version comparison.
Return (comparison string, StrictVersion)
"""
res = re_splitComparison.match(pred)
if not res:
raise ValueError("bad package restriction syntax: %r" % pred)
comp, verStr = res.groups()
return (comp, distutils.version.StrictVersion(verStr))
compmap = {"<": operator.lt, "<=": operator.le, "==": operator.eq,
">": operator.gt, ">=": operator.ge, "!=": operator.ne}
class VersionPredicate:
"""Parse and test package version predicates.
>>> v = VersionPredicate('pyepat.abc (>1.0, <3333.3a1, !=1555.1b3)')
The `name` attribute provides the full dotted name that is given::
>>> v.name
'pyepat.abc'
The str() of a `VersionPredicate` provides a normalized
human-readable version of the expression::
>>> print(v)
pyepat.abc (> 1.0, < 3333.3a1, != 1555.1b3)
The `satisfied_by()` method can be used to determine with a given
version number is included in the set described by the version
restrictions::
>>> v.satisfied_by('1.1')
True
>>> v.satisfied_by('1.4')
True
>>> v.satisfied_by('1.0')
False
>>> v.satisfied_by('4444.4')
False
>>> v.satisfied_by('1555.1b3')
False
`VersionPredicate` is flexible in accepting extra whitespace::
>>> v = VersionPredicate(' pat( == 0.1 ) ')
>>> v.name
'pat'
>>> v.satisfied_by('0.1')
True
>>> v.satisfied_by('0.2')
False
If any version numbers passed in do not conform to the
restrictions of `StrictVersion`, a `ValueError` is raised::
>>> v = VersionPredicate('p1.p2.p3.p4(>=1.0, <=1.3a1, !=1.2zb3)')
Traceback (most recent call last):
...
ValueError: invalid version number '1.2zb3'
It the module or package name given does not conform to what's
allowed as a legal module or package name, `ValueError` is
raised::
>>> v = VersionPredicate('foo-bar')
Traceback (most recent call last):
...
ValueError: expected parenthesized list: '-bar'
>>> v = VersionPredicate('foo bar (12.21)')
Traceback (most recent call last):
...
ValueError: expected parenthesized list: 'bar (12.21)'
"""
def __init__(self, versionPredicateStr):
"""Parse a version predicate string.
"""
# Fields:
# name: package name
# pred: list of (comparison string, StrictVersion)
versionPredicateStr = versionPredicateStr.strip()
if not versionPredicateStr:
raise ValueError("empty package restriction")
match = re_validPackage.match(versionPredicateStr)
if not match:
raise ValueError("bad package name in %r" % versionPredicateStr)
self.name, paren = match.groups()
paren = paren.strip()
if paren:
match = re_paren.match(paren)
if not match:
raise ValueError("expected parenthesized list: %r" % paren)
str = match.groups()[0]
self.pred = [splitUp(aPred) for aPred in str.split(",")]
if not self.pred:
raise ValueError("empty parenthesized list in %r"
% versionPredicateStr)
else:
self.pred = []
def __str__(self):
if self.pred:
seq = [cond + " " + str(ver) for cond, ver in self.pred]
return self.name + " (" + ", ".join(seq) + ")"
else:
return self.name
def satisfied_by(self, version):
"""True if version is compatible with all the predicates in self.
The parameter version must be acceptable to the StrictVersion
constructor. It may be either a string or StrictVersion.
"""
for cond, ver in self.pred:
if not compmap[cond](version, ver):
return False
return True
_provision_rx = None
def split_provision(value):
"""Return the name and optional version number of a provision.
The version number, if given, will be returned as a `StrictVersion`
instance, otherwise it will be `None`.
>>> split_provision('mypkg')
('mypkg', None)
>>> split_provision(' mypkg( 1.2 ) ')
('mypkg', StrictVersion ('1.2'))
"""
global _provision_rx
if _provision_rx is None:
_provision_rx = re.compile(
r"([a-zA-Z_]\w*(?:\.[a-zA-Z_]\w*)*)(?:\s*\(\s*([^)\s]+)\s*\))?$",
re.ASCII)
value = value.strip()
m = _provision_rx.match(value)
if not m:
raise ValueError("illegal provides specification: %r" % value)
ver = m.group(2) or None
if ver:
ver = distutils.version.StrictVersion(ver)
return m.group(1), ver
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