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: 2,519 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 | from distutils import log
import distutils.command.install_scripts as orig
import os
import sys
from pkg_resources import Distribution, PathMetadata, ensure_directory
class install_scripts(orig.install_scripts):
"""Do normal script install, plus any egg_info wrapper scripts"""
def initialize_options(self):
orig.install_scripts.initialize_options(self)
self.no_ep = False
def run(self):
import setuptools.command.easy_install as ei
self.run_command("egg_info")
if self.distribution.scripts:
orig.install_scripts.run(self) # run first to set up self.outfiles
else:
self.outfiles = []
if self.no_ep:
# don't install entry point scripts into .egg file!
return
ei_cmd = self.get_finalized_command("egg_info")
dist = Distribution(
ei_cmd.egg_base, PathMetadata(ei_cmd.egg_base, ei_cmd.egg_info),
ei_cmd.egg_name, ei_cmd.egg_version,
)
bs_cmd = self.get_finalized_command('build_scripts')
exec_param = getattr(bs_cmd, 'executable', None)
try:
bw_cmd = self.get_finalized_command("bdist_wininst")
is_wininst = getattr(bw_cmd, '_is_running', False)
except ImportError:
is_wininst = False
writer = ei.ScriptWriter
if is_wininst:
exec_param = "python.exe"
writer = ei.WindowsScriptWriter
if exec_param == sys.executable:
# In case the path to the Python executable contains a space, wrap
# it so it's not split up.
exec_param = [exec_param]
# resolve the writer to the environment
writer = writer.best()
cmd = writer.command_spec_class.best().from_param(exec_param)
for args in writer.get_args(dist, cmd.as_header()):
self.write_script(*args)
def write_script(self, script_name, contents, mode="t", *ignored):
"""Write an executable file to the scripts directory"""
from setuptools.command.easy_install import chmod, current_umask
log.info("Installing %s script to %s", script_name, self.install_dir)
target = os.path.join(self.install_dir, script_name)
self.outfiles.append(target)
mask = current_umask()
if not self.dry_run:
ensure_directory(target)
f = open(target, "w" + mode)
f.write(contents)
f.close()
chmod(target, 0o777 - mask)
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