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
| import zipfile | |
| import fsspec | |
| from fsspec.archive import AbstractArchiveFileSystem | |
| class ZipFileSystem(AbstractArchiveFileSystem): | |
| """Read/Write contents of ZIP archive as a file-system | |
| Keeps file object open while instance lives. | |
| This class is pickleable, but not necessarily thread-safe | |
| """ | |
| root_marker = "" | |
| protocol = "zip" | |
| cachable = False | |
| def __init__( | |
| self, | |
| fo="", | |
| mode="r", | |
| target_protocol=None, | |
| target_options=None, | |
| compression=zipfile.ZIP_STORED, | |
| allowZip64=True, | |
| compresslevel=None, | |
| **kwargs, | |
| ): | |
| """ | |
| Parameters | |
| ---------- | |
| fo: str or file-like | |
| Contains ZIP, and must exist. If a str, will fetch file using | |
| :meth:`~fsspec.open_files`, which must return one file exactly. | |
| mode: str | |
| Accept: "r", "w", "a" | |
| target_protocol: str (optional) | |
| If ``fo`` is a string, this value can be used to override the | |
| FS protocol inferred from a URL | |
| target_options: dict (optional) | |
| Kwargs passed when instantiating the target FS, if ``fo`` is | |
| a string. | |
| compression, allowZip64, compresslevel: passed to ZipFile | |
| Only relevant when creating a ZIP | |
| """ | |
| super().__init__(self, **kwargs) | |
| if mode not in set("rwa"): | |
| raise ValueError(f"mode '{mode}' no understood") | |
| self.mode = mode | |
| if isinstance(fo, str): | |
| if mode == "a": | |
| m = "r+b" | |
| else: | |
| m = mode + "b" | |
| fo = fsspec.open( | |
| fo, mode=m, protocol=target_protocol, **(target_options or {}) | |
| ) | |
| self.of = fo | |
| self.fo = fo.__enter__() # the whole instance is a context | |
| self.zip = zipfile.ZipFile( | |
| self.fo, | |
| mode=mode, | |
| compression=compression, | |
| allowZip64=allowZip64, | |
| compresslevel=compresslevel, | |
| ) | |
| self.dir_cache = None | |
| def _strip_protocol(cls, path): | |
| # zip file paths are always relative to the archive root | |
| return super()._strip_protocol(path).lstrip("/") | |
| def __del__(self): | |
| if hasattr(self, "zip"): | |
| self.close() | |
| del self.zip | |
| def close(self): | |
| """Commits any write changes to the file. Done on ``del`` too.""" | |
| self.zip.close() | |
| def _get_dirs(self): | |
| if self.dir_cache is None or self.mode in set("wa"): | |
| # when writing, dir_cache is always in the ZipFile's attributes, | |
| # not read from the file. | |
| files = self.zip.infolist() | |
| self.dir_cache = { | |
| dirname.rstrip("/"): { | |
| "name": dirname.rstrip("/"), | |
| "size": 0, | |
| "type": "directory", | |
| } | |
| for dirname in self._all_dirnames(self.zip.namelist()) | |
| } | |
| for z in files: | |
| f = {s: getattr(z, s, None) for s in zipfile.ZipInfo.__slots__} | |
| f.update( | |
| { | |
| "name": z.filename.rstrip("/"), | |
| "size": z.file_size, | |
| "type": ("directory" if z.is_dir() else "file"), | |
| } | |
| ) | |
| self.dir_cache[f["name"]] = f | |
| def pipe_file(self, path, value, **kwargs): | |
| # override upstream, because we know the exact file size in this case | |
| self.zip.writestr(path, value, **kwargs) | |
| def _open( | |
| self, | |
| path, | |
| mode="rb", | |
| block_size=None, | |
| autocommit=True, | |
| cache_options=None, | |
| **kwargs, | |
| ): | |
| path = self._strip_protocol(path) | |
| if "r" in mode and self.mode in set("wa"): | |
| if self.exists(path): | |
| raise OSError("ZipFS can only be open for reading or writing, not both") | |
| raise FileNotFoundError(path) | |
| if "r" in self.mode and "w" in mode: | |
| raise OSError("ZipFS can only be open for reading or writing, not both") | |
| out = self.zip.open(path, mode.strip("b")) | |
| if "r" in mode: | |
| info = self.info(path) | |
| out.size = info["size"] | |
| out.name = info["name"] | |
| return out | |