Safetensors
GGUF
Turkish
llama
Llama-3
instruct
finetune
chatml
gpt4
synthetic data
distillation
function calling
json mode
axolotl
roleplaying
chat
Instructions to use tda45/TdAI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use tda45/TdAI with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="tda45/TdAI", filename="llama.cpp/models/ggml-vocab-aquila.gguf", )
output = llm( "Once upon a time,", max_tokens=512, echo=True ) print(output)
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use tda45/TdAI 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 tda45/TdAI # Run inference directly in the terminal: llama cli -hf tda45/TdAI
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf tda45/TdAI # Run inference directly in the terminal: llama cli -hf tda45/TdAI
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 tda45/TdAI # Run inference directly in the terminal: ./llama-cli -hf tda45/TdAI
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 tda45/TdAI # Run inference directly in the terminal: ./build/bin/llama-cli -hf tda45/TdAI
Use Docker
docker model run hf.co/tda45/TdAI
- LM Studio
- Jan
- Ollama
How to use tda45/TdAI with Ollama:
ollama run hf.co/tda45/TdAI
- Unsloth Studio
How to use tda45/TdAI 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 tda45/TdAI 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 tda45/TdAI to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for tda45/TdAI to start chatting
- Atomic Chat new
- Docker Model Runner
How to use tda45/TdAI with Docker Model Runner:
docker model run hf.co/tda45/TdAI
- Lemonade
How to use tda45/TdAI with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull tda45/TdAI
Run and chat with the model
lemonade run user.TdAI-{{QUANT_TAG}}List all available models
lemonade list
| #!/usr/bin/env python3 | |
| """ | |
| # Generated by Claude AI | |
| Script to completely regenerate the GGML remoting codebase from YAML configuration. | |
| This script reads api_functions.yaml and regenerates all the header files and | |
| implementation templates for the GGML remoting layer. | |
| Usage: | |
| python regenerate_remoting.py | |
| The script will: | |
| 1. Read ggmlremoting_functions.yaml configuration | |
| 2. Generate updated header files | |
| 3. Generate implementation templates in dedicated files | |
| 4. Show a summary of what was generated | |
| """ | |
| import yaml | |
| from typing import Dict, List, Any | |
| from pathlib import Path | |
| import os | |
| import subprocess | |
| import shutil | |
| import logging | |
| NL = '\n' # can't have f"{'\n'}" in f-strings | |
| class RemotingCodebaseGenerator: | |
| def __init__(self, yaml_path: str = "ggmlremoting_functions.yaml"): | |
| """Initialize the generator with the YAML configuration.""" | |
| self.yaml_path = yaml_path | |
| if not Path(yaml_path).exists(): | |
| raise FileNotFoundError(f"Configuration file {yaml_path} not found") | |
| with open(yaml_path, 'r') as f: | |
| self.config = yaml.safe_load(f) | |
| self.functions = self.config['functions'] | |
| self.naming_patterns = self.config['naming_patterns'] | |
| self.config_data = self.config['config'] | |
| # Check if clang-format is available | |
| self.clang_format_available = self._check_clang_format_available() | |
| def _check_clang_format_available(self) -> bool: | |
| """Check if clang-format is available in the system PATH.""" | |
| return shutil.which("clang-format") is not None | |
| def _format_file_with_clang_format(self, file_path: Path) -> bool: | |
| """Format a file with clang-format -i. Returns True if successful, False otherwise.""" | |
| if not self.clang_format_available: | |
| return False | |
| try: | |
| subprocess.run( | |
| ["clang-format", "-i", str(file_path)], | |
| check=True, | |
| capture_output=True, | |
| text=True | |
| ) | |
| return True | |
| except subprocess.CalledProcessError: | |
| logging.exception(f" โ ๏ธ clang-format failed for {file_path}") | |
| return False | |
| except Exception as e: | |
| logging.exception(f" โ ๏ธ Unexpected error formatting {file_path}: {e}") | |
| return False | |
| def generate_enum_name(self, group_name: str, function_name: str) -> str: | |
| """Generate the APIR_COMMAND_TYPE enum name for a function.""" | |
| prefix = self.naming_patterns['enum_prefix'] | |
| return f"{prefix}{group_name.upper()}_{function_name.upper()}" | |
| def generate_backend_function_name(self, group_name: str, function_name: str) -> str: | |
| """Generate the backend function name.""" | |
| function_key = f"{group_name}_{function_name}" | |
| overrides = self.naming_patterns.get('backend_function_overrides', {}) | |
| if function_key in overrides: | |
| return overrides[function_key] | |
| prefix = self.naming_patterns['backend_function_prefix'] | |
| return f"{prefix}{group_name}_{function_name}" | |
| def generate_frontend_function_name(self, group_name: str, function_name: str) -> str: | |
| """Generate the frontend function name.""" | |
| prefix = self.naming_patterns['frontend_function_prefix'] | |
| return f"{prefix}{group_name}_{function_name}" | |
| def get_enabled_functions(self) -> List[Dict[str, Any]]: | |
| """Get all enabled functions with their metadata.""" | |
| functions = [] | |
| enum_value = 0 | |
| for group_name, group_data in self.functions.items(): | |
| group_description = group_data['group_description'] | |
| for function_name, func_metadata in group_data['functions'].items(): | |
| # Handle case where func_metadata is None or empty (functions with only comments) | |
| if func_metadata is None: | |
| func_metadata = {} | |
| # Functions are enabled by default unless explicitly disabled | |
| if func_metadata.get('enabled', True): | |
| functions.append({ | |
| 'group_name': group_name, | |
| 'function_name': function_name, | |
| 'enum_name': self.generate_enum_name(group_name, function_name), | |
| 'enum_value': enum_value, | |
| 'backend_function': self.generate_backend_function_name(group_name, function_name), | |
| 'frontend_function': self.generate_frontend_function_name(group_name, function_name), | |
| 'frontend_return': func_metadata.get('frontend_return', 'void'), | |
| 'frontend_extra_params': func_metadata.get('frontend_extra_params', []), | |
| 'group_description': group_description, | |
| 'deprecated': func_metadata.get('deprecated', False), | |
| }) | |
| enum_value += 1 | |
| return functions | |
| def generate_apir_backend_header(self) -> str: | |
| """Generate the complete apir_backend.h file.""" | |
| functions = self.get_enabled_functions() | |
| # Generate the enum section | |
| enum_lines = ["typedef enum ApirBackendCommandType {"] | |
| current_group = None | |
| for func in functions: | |
| # Add comment for new group | |
| if func['group_name'] != current_group: | |
| enum_lines.append("") | |
| enum_lines.append(f" /* {func['group_description']} */") | |
| current_group = func['group_name'] | |
| enum_lines.append(f" {func['enum_name']} = {func['enum_value']},") | |
| # Add the count | |
| total_count = len(functions) | |
| enum_lines.append("\n // last command_type index + 1") | |
| enum_lines.append(f" APIR_BACKEND_DISPATCH_TABLE_COUNT = {total_count},") | |
| enum_lines.append("} ApirBackendCommandType;") | |
| # Generate function name mapping | |
| func_lines = [] | |
| func_lines.append("static inline const char * apir_dispatch_command_name(ApirBackendCommandType type) {") | |
| func_lines.append(" switch (type) {") | |
| current_group = None | |
| for func in functions: | |
| # Add comment for new group | |
| if func['group_name'] != current_group: | |
| func_lines.append(f" /* {func['group_description']} */") | |
| current_group = func['group_name'] | |
| # Generate clean function name without backend_ prefix | |
| clean_name = f"{func['group_name']}_{func['function_name']}" | |
| func_lines.append(f" case {func['enum_name']}:") | |
| func_lines.append(f" return \"{clean_name}\";") | |
| func_lines.append("") | |
| func_lines.append(" default:") | |
| func_lines.append(" return \"unknown\";") | |
| func_lines.append(" }") | |
| func_lines.append("}") | |
| # Full header template | |
| header_content = NL.join(enum_lines) + "\n\n" + NL.join(func_lines) + "\n" | |
| return header_content | |
| def generate_backend_dispatched_header(self) -> str: | |
| """Generate the complete backend-dispatched.h file.""" | |
| functions = self.get_enabled_functions() | |
| # Function declarations | |
| decl_lines = [] | |
| current_group = None | |
| for func in functions: | |
| if func['group_name'] != current_group: | |
| decl_lines.append(f"\n/* {func['group_description']} */") | |
| current_group = func['group_name'] | |
| signature = "uint32_t" | |
| params = "apir_encoder *enc, apir_decoder *dec, virgl_apir_context *ctx" | |
| if func['deprecated']: | |
| decl_lines.append(f"/* {func['enum_name']} is deprecated. Keeping the handler for backward compatibility. */") | |
| decl_lines.append(f"{signature} {func['backend_function']}({params});") | |
| # Dispatch table | |
| table_lines = [] | |
| current_group = None | |
| for func in functions: | |
| if func['group_name'] != current_group: | |
| table_lines.append(f"\n /* {func['group_description']} */") | |
| table_lines.append("") | |
| current_group = func['group_name'] | |
| deprecated = " /* DEPRECATED */" if func['deprecated'] else "" | |
| table_lines.append(f" /* {func['enum_name']} = */ {func['backend_function']}{deprecated},") | |
| header_content = f'''\ | |
| #pragma once | |
| {NL.join(decl_lines)} | |
| extern "C" {{ | |
| static const backend_dispatch_t apir_backend_dispatch_table[APIR_BACKEND_DISPATCH_TABLE_COUNT] = {{ | |
| {NL.join(table_lines)} | |
| }}; | |
| }} | |
| ''' | |
| return header_content | |
| def generate_virtgpu_forward_header(self) -> str: | |
| """Generate the complete virtgpu-forward.gen.h file.""" | |
| functions = self.get_enabled_functions() | |
| decl_lines = [] | |
| current_group = None | |
| for func in functions: | |
| if func['group_name'] != current_group: | |
| decl_lines.append("") | |
| decl_lines.append(f"/* {func['group_description']} */") | |
| current_group = func['group_name'] | |
| if func['deprecated']: | |
| decl_lines.append(f"/* {func['frontend_function']} is deprecated. */") | |
| continue | |
| # Build parameter list | |
| params = [self.naming_patterns['frontend_base_param']] | |
| params.extend(func['frontend_extra_params']) | |
| param_str = ', '.join(params) | |
| decl_lines.append(f"{func['frontend_return']} {func['frontend_function']}({param_str});") | |
| header_content = f'''\ | |
| #pragma once | |
| {NL.join(decl_lines)} | |
| ''' | |
| return header_content | |
| def regenerate_codebase(self) -> None: | |
| """Regenerate the entire remoting codebase.""" | |
| logging.info("๐ Regenerating GGML Remoting Codebase...") | |
| logging.info("=" * 50) | |
| # Detect if we're running from frontend directory | |
| current_dir = os.getcwd() | |
| is_frontend_dir = current_dir.endswith('ggml-virtgpu') | |
| if is_frontend_dir: | |
| # Running from ggml/src/ggml-virtgpu-apir | |
| logging.info("๐ Detected frontend directory execution") | |
| frontend_base = Path(".") | |
| else: | |
| # Running from project root (fallback to original behavior) | |
| logging.info("๐ Detected project root execution") | |
| base_path = self.config_data.get('base_path', 'ggml/src') | |
| frontend_base = Path(base_path) / "ggml-virtgpu" | |
| # Compute final file paths | |
| backend_base = frontend_base / "backend" | |
| apir_backend_path = backend_base / "shared" / "apir_backend.gen.h" | |
| backend_dispatched_path = backend_base / "backend-dispatched.gen.h" | |
| virtgpu_forward_path = frontend_base / "virtgpu-forward.gen.h" | |
| # Create output directories for each file | |
| apir_backend_path.parent.mkdir(parents=True, exist_ok=True) | |
| backend_dispatched_path.parent.mkdir(parents=True, exist_ok=True) | |
| virtgpu_forward_path.parent.mkdir(parents=True, exist_ok=True) | |
| # Generate header files | |
| logging.info("๐ Generating header files...") | |
| apir_backend_content = self.generate_apir_backend_header() | |
| apir_backend_path.write_text(apir_backend_content) | |
| logging.info(f" โ {apir_backend_path.resolve()}") | |
| backend_dispatched_content = self.generate_backend_dispatched_header() | |
| backend_dispatched_path.write_text(backend_dispatched_content) | |
| logging.info(f" โ {backend_dispatched_path.resolve()}") | |
| virtgpu_forward_content = self.generate_virtgpu_forward_header() | |
| virtgpu_forward_path.write_text(virtgpu_forward_content) | |
| logging.info(f" โ {virtgpu_forward_path.resolve()}") | |
| # Format generated files with clang-format | |
| generated_files = [apir_backend_path, backend_dispatched_path, virtgpu_forward_path] | |
| if not self.clang_format_available: | |
| logging.warning("\nโ ๏ธclang-format not found in PATH. Generated files will not be formatted.\n" | |
| " Install clang-format to enable automatic code formatting.") | |
| else: | |
| logging.info("\n๐จ Formatting files with clang-format...") | |
| for file_path in generated_files: | |
| if self._format_file_with_clang_format(file_path): | |
| logging.info(f" โ Formatted {file_path.name}") | |
| else: | |
| logging.warning(f" โ Failed to format {file_path.name}") | |
| # Generate summary | |
| functions = self.get_enabled_functions() | |
| total_functions = len(functions) | |
| logging.info("\n๐ Generation Summary:") | |
| logging.info("=" * 50) | |
| logging.info(f" Total functions: {total_functions}") | |
| logging.info(f" Function groups: {len(self.functions)}") | |
| logging.info(" Header files: 3") | |
| logging.info(f" Working directory: {current_dir}") | |
| def main(): | |
| try: | |
| generator = RemotingCodebaseGenerator() | |
| generator.regenerate_codebase() | |
| except Exception as e: | |
| logging.exception(f"โ Error: {e}") | |
| exit(1) | |
| if __name__ == "__main__": | |
| main() | |