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
| namespace jinja { | |
| // | |
| // string_part | |
| // | |
| bool string_part::is_uppercase() const { | |
| for (char c : val) { | |
| if (std::islower(static_cast<unsigned char>(c))) { | |
| return false; | |
| } | |
| } | |
| return true; | |
| } | |
| bool string_part::is_lowercase() const { | |
| for (char c : val) { | |
| if (std::isupper(static_cast<unsigned char>(c))) { | |
| return false; | |
| } | |
| } | |
| return true; | |
| } | |
| // | |
| // string | |
| // | |
| void string::mark_input() { | |
| for (auto & part : parts) { | |
| part.is_input = true; | |
| } | |
| } | |
| std::string string::str() const { | |
| if (parts.size() == 1) { | |
| return parts[0].val; | |
| } | |
| std::ostringstream oss; | |
| for (const auto & part : parts) { | |
| oss << part.val; | |
| } | |
| return oss.str(); | |
| } | |
| size_t string::length() const { | |
| size_t len = 0; | |
| for (const auto & part : parts) { | |
| len += part.val.length(); | |
| } | |
| return len; | |
| } | |
| void string::hash_update(hasher & hash) const noexcept { | |
| for (const auto & part : parts) { | |
| hash.update(part.val.data(), part.val.length()); | |
| } | |
| } | |
| bool string::all_parts_are_input() const { | |
| for (const auto & part : parts) { | |
| if (!part.is_input) { | |
| return false; | |
| } | |
| } | |
| return true; | |
| } | |
| bool string::is_uppercase() const { | |
| for (const auto & part : parts) { | |
| if (!part.is_uppercase()) { | |
| return false; | |
| } | |
| } | |
| return true; | |
| } | |
| bool string::is_lowercase() const { | |
| for (const auto & part : parts) { | |
| if (!part.is_lowercase()) { | |
| return false; | |
| } | |
| } | |
| return true; | |
| } | |
| // mark this string as input if other has ALL parts as input | |
| void string::mark_input_based_on(const string & other) { | |
| if (other.all_parts_are_input()) { | |
| for (auto & part : parts) { | |
| part.is_input = true; | |
| } | |
| } | |
| } | |
| string string::append(const string & other) { | |
| for (const auto & part : other.parts) { | |
| parts.push_back(part); | |
| } | |
| return *this; | |
| } | |
| // in-place transformation | |
| using transform_fn = std::function<std::string(const std::string&)>; | |
| static string apply_transform(string & self, const transform_fn & fn) { | |
| for (auto & part : self.parts) { | |
| part.val = fn(part.val); | |
| } | |
| return self; | |
| } | |
| string string::uppercase() { | |
| return apply_transform(*this, [](const std::string & s) { | |
| std::string res = s; | |
| std::transform(res.begin(), res.end(), res.begin(), ::toupper); | |
| return res; | |
| }); | |
| } | |
| string string::lowercase() { | |
| return apply_transform(*this, [](const std::string & s) { | |
| std::string res = s; | |
| std::transform(res.begin(), res.end(), res.begin(), ::tolower); | |
| return res; | |
| }); | |
| } | |
| string string::capitalize() { | |
| return apply_transform(*this, [](const std::string & s) { | |
| if (s.empty()) return s; | |
| std::string res = s; | |
| res[0] = ::toupper(static_cast<unsigned char>(res[0])); | |
| std::transform(res.begin() + 1, res.end(), res.begin() + 1, ::tolower); | |
| return res; | |
| }); | |
| } | |
| string string::titlecase() { | |
| return apply_transform(*this, [](const std::string & s) { | |
| std::string res = s; | |
| bool capitalize_next = true; | |
| for (char &c : res) { | |
| if (isspace(static_cast<unsigned char>(c))) { | |
| capitalize_next = true; | |
| } else if (capitalize_next) { | |
| c = ::toupper(static_cast<unsigned char>(c)); | |
| capitalize_next = false; | |
| } else { | |
| c = ::tolower(static_cast<unsigned char>(c)); | |
| } | |
| } | |
| return res; | |
| }); | |
| } | |
| string string::strip(bool left, bool right, std::optional<const std::string_view> chars) { | |
| static auto strip_part = [](const std::string & s, bool left, bool right, std::optional<const std::string_view> chars) -> std::string { | |
| size_t start = 0; | |
| size_t end = s.length(); | |
| auto match_char = [&chars](unsigned char c) -> bool { | |
| return chars ? (*chars).find(c) != std::string::npos : isspace(c); | |
| }; | |
| if (left) { | |
| while (start < end && match_char(static_cast<unsigned char>(s[start]))) { | |
| ++start; | |
| } | |
| } | |
| if (right) { | |
| while (end > start && match_char(static_cast<unsigned char>(s[end - 1]))) { | |
| --end; | |
| } | |
| } | |
| return s.substr(start, end - start); | |
| }; | |
| if (parts.empty()) { | |
| return *this; | |
| } | |
| if (left) { | |
| for (size_t i = 0; i < parts.size(); ++i) { | |
| parts[i].val = strip_part(parts[i].val, true, false, chars); | |
| if (parts[i].val.empty()) { | |
| // remove empty part | |
| parts.erase(parts.begin() + i); | |
| --i; | |
| continue; | |
| } else { | |
| break; | |
| } | |
| } | |
| } | |
| if (right) { | |
| for (size_t i = parts.size(); i-- > 0;) { | |
| parts[i].val = strip_part(parts[i].val, false, true, chars); | |
| if (parts[i].val.empty()) { | |
| // remove empty part | |
| parts.erase(parts.begin() + i); | |
| continue; | |
| } else { | |
| break; | |
| } | |
| } | |
| } | |
| return *this; | |
| } | |
| } // namespace jinja | |