Instructions to use vidfom/Ltx-3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use vidfom/Ltx-3 with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="vidfom/Ltx-3", filename="ComfyUI/models/text_encoders/gemma-3-12b-it-qat-UD-Q4_K_XL.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use vidfom/Ltx-3 with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf vidfom/Ltx-3:UD-Q4_K_XL # Run inference directly in the terminal: llama-cli -hf vidfom/Ltx-3:UD-Q4_K_XL
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf vidfom/Ltx-3:UD-Q4_K_XL # Run inference directly in the terminal: llama-cli -hf vidfom/Ltx-3:UD-Q4_K_XL
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 vidfom/Ltx-3:UD-Q4_K_XL # Run inference directly in the terminal: ./llama-cli -hf vidfom/Ltx-3:UD-Q4_K_XL
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 vidfom/Ltx-3:UD-Q4_K_XL # Run inference directly in the terminal: ./build/bin/llama-cli -hf vidfom/Ltx-3:UD-Q4_K_XL
Use Docker
docker model run hf.co/vidfom/Ltx-3:UD-Q4_K_XL
- LM Studio
- Jan
- Ollama
How to use vidfom/Ltx-3 with Ollama:
ollama run hf.co/vidfom/Ltx-3:UD-Q4_K_XL
- Unsloth Studio new
How to use vidfom/Ltx-3 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 vidfom/Ltx-3 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 vidfom/Ltx-3 to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for vidfom/Ltx-3 to start chatting
- Docker Model Runner
How to use vidfom/Ltx-3 with Docker Model Runner:
docker model run hf.co/vidfom/Ltx-3:UD-Q4_K_XL
- Lemonade
How to use vidfom/Ltx-3 with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull vidfom/Ltx-3:UD-Q4_K_XL
Run and chat with the model
lemonade run user.Ltx-3-UD-Q4_K_XL
List all available models
lemonade list
| import logging | |
| import os | |
| import uuid | |
| from typing import Callable | |
| from aiohttp import web | |
| import folder_paths | |
| from app.assets.api.schemas_in import ParsedUpload, UploadError | |
| from app.assets.helpers import validate_blake3_hash | |
| def normalize_and_validate_hash(s: str) -> str: | |
| """Validate and normalize a hash string. | |
| Returns canonical 'blake3:<hex>' or raises UploadError. | |
| """ | |
| try: | |
| return validate_blake3_hash(s) | |
| except ValueError: | |
| raise UploadError(400, "INVALID_HASH", "hash must be like 'blake3:<hex>'") | |
| async def parse_multipart_upload( | |
| request: web.Request, | |
| check_hash_exists: Callable[[str], bool], | |
| ) -> ParsedUpload: | |
| """ | |
| Parse a multipart/form-data upload request. | |
| Args: | |
| request: The aiohttp request | |
| check_hash_exists: Callable(hash_str) -> bool to check if a hash exists | |
| Returns: | |
| ParsedUpload with parsed fields and temp file path | |
| Raises: | |
| UploadError: On validation or I/O errors | |
| """ | |
| if not (request.content_type or "").lower().startswith("multipart/"): | |
| raise UploadError( | |
| 415, "UNSUPPORTED_MEDIA_TYPE", "Use multipart/form-data for uploads." | |
| ) | |
| reader = await request.multipart() | |
| file_present = False | |
| file_client_name: str | None = None | |
| tags_raw: list[str] = [] | |
| provided_name: str | None = None | |
| user_metadata_raw: str | None = None | |
| provided_hash: str | None = None | |
| provided_hash_exists: bool | None = None | |
| provided_mime_type: str | None = None | |
| provided_preview_id: str | None = None | |
| file_written = 0 | |
| tmp_path: str | None = None | |
| while True: | |
| field = await reader.next() | |
| if field is None: | |
| break | |
| fname = getattr(field, "name", "") or "" | |
| if fname == "hash": | |
| try: | |
| s = ((await field.text()) or "").strip().lower() | |
| except Exception: | |
| raise UploadError( | |
| 400, "INVALID_HASH", "hash must be like 'blake3:<hex>'" | |
| ) | |
| if s: | |
| provided_hash = normalize_and_validate_hash(s) | |
| try: | |
| provided_hash_exists = check_hash_exists(provided_hash) | |
| except Exception as e: | |
| logging.exception( | |
| "check_hash_exists failed for hash=%s: %s", provided_hash, e | |
| ) | |
| raise UploadError( | |
| 500, | |
| "HASH_CHECK_FAILED", | |
| "Backend error while checking asset hash.", | |
| ) | |
| elif fname == "file": | |
| file_present = True | |
| file_client_name = (field.filename or "").strip() | |
| if provided_hash and provided_hash_exists is True: | |
| # Hash exists - drain file but don't write to disk | |
| try: | |
| while True: | |
| chunk = await field.read_chunk(8 * 1024 * 1024) | |
| if not chunk: | |
| break | |
| file_written += len(chunk) | |
| except Exception: | |
| raise UploadError( | |
| 500, "UPLOAD_IO_ERROR", "Failed to receive uploaded file." | |
| ) | |
| continue | |
| uploads_root = os.path.join(folder_paths.get_temp_directory(), "uploads") | |
| unique_dir = os.path.join(uploads_root, uuid.uuid4().hex) | |
| os.makedirs(unique_dir, exist_ok=True) | |
| tmp_path = os.path.join(unique_dir, ".upload.part") | |
| try: | |
| with open(tmp_path, "wb") as f: | |
| while True: | |
| chunk = await field.read_chunk(8 * 1024 * 1024) | |
| if not chunk: | |
| break | |
| f.write(chunk) | |
| file_written += len(chunk) | |
| except Exception: | |
| delete_temp_file_if_exists(tmp_path) | |
| raise UploadError( | |
| 500, "UPLOAD_IO_ERROR", "Failed to receive and store uploaded file." | |
| ) | |
| elif fname == "tags": | |
| tags_raw.append((await field.text()) or "") | |
| elif fname == "name": | |
| provided_name = (await field.text()) or None | |
| elif fname == "user_metadata": | |
| user_metadata_raw = (await field.text()) or None | |
| elif fname == "id": | |
| raise UploadError( | |
| 400, | |
| "UNSUPPORTED_FIELD", | |
| "Client-provided 'id' is not supported. Asset IDs are assigned by the server.", | |
| ) | |
| elif fname == "mime_type": | |
| provided_mime_type = ((await field.text()) or "").strip() or None | |
| elif fname == "preview_id": | |
| provided_preview_id = ((await field.text()) or "").strip() or None | |
| if not file_present and not (provided_hash and provided_hash_exists): | |
| raise UploadError( | |
| 400, "MISSING_FILE", "Form must include a 'file' part or a known 'hash'." | |
| ) | |
| if ( | |
| file_present | |
| and file_written == 0 | |
| and not (provided_hash and provided_hash_exists) | |
| ): | |
| delete_temp_file_if_exists(tmp_path) | |
| raise UploadError(400, "EMPTY_UPLOAD", "Uploaded file is empty.") | |
| return ParsedUpload( | |
| file_present=file_present, | |
| file_written=file_written, | |
| file_client_name=file_client_name, | |
| tmp_path=tmp_path, | |
| tags_raw=tags_raw, | |
| provided_name=provided_name, | |
| user_metadata_raw=user_metadata_raw, | |
| provided_hash=provided_hash, | |
| provided_hash_exists=provided_hash_exists, | |
| provided_mime_type=provided_mime_type, | |
| provided_preview_id=provided_preview_id, | |
| ) | |
| def delete_temp_file_if_exists(tmp_path: str | None) -> None: | |
| """Safely remove a temp file and its parent directory if empty.""" | |
| if tmp_path: | |
| try: | |
| if os.path.exists(tmp_path): | |
| os.remove(tmp_path) | |
| except OSError as e: | |
| logging.debug("Failed to delete temp file %s: %s", tmp_path, e) | |
| try: | |
| parent = os.path.dirname(tmp_path) | |
| if parent and os.path.isdir(parent): | |
| os.rmdir(parent) # only succeeds if empty | |
| except OSError: | |
| pass | |