Transformers
PyTorch
Safetensors
GGUF
English
llama
text-generation-inference
unsloth
trl
sft
8-bit precision
Instructions to use DeveloperZoyel/model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DeveloperZoyel/model with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("DeveloperZoyel/model", dtype="auto") - llama-cpp-python
How to use DeveloperZoyel/model with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="DeveloperZoyel/model", filename="unsloth.Q8_0.gguf", )
output = llm( "Once upon a time,", max_tokens=512, echo=True ) print(output)
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use DeveloperZoyel/model with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf DeveloperZoyel/model:Q8_0 # Run inference directly in the terminal: llama-cli -hf DeveloperZoyel/model:Q8_0
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf DeveloperZoyel/model:Q8_0 # Run inference directly in the terminal: llama-cli -hf DeveloperZoyel/model:Q8_0
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 DeveloperZoyel/model:Q8_0 # Run inference directly in the terminal: ./llama-cli -hf DeveloperZoyel/model:Q8_0
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 DeveloperZoyel/model:Q8_0 # Run inference directly in the terminal: ./build/bin/llama-cli -hf DeveloperZoyel/model:Q8_0
Use Docker
docker model run hf.co/DeveloperZoyel/model:Q8_0
- LM Studio
- Jan
- Ollama
How to use DeveloperZoyel/model with Ollama:
ollama run hf.co/DeveloperZoyel/model:Q8_0
- Unsloth Studio new
How to use DeveloperZoyel/model 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 DeveloperZoyel/model 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 DeveloperZoyel/model to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for DeveloperZoyel/model to start chatting
- Docker Model Runner
How to use DeveloperZoyel/model with Docker Model Runner:
docker model run hf.co/DeveloperZoyel/model:Q8_0
- Lemonade
How to use DeveloperZoyel/model with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull DeveloperZoyel/model:Q8_0
Run and chat with the model
lemonade run user.model-Q8_0
List all available models
lemonade list
| { | |
| "_name_or_path": "unsloth/meta-llama-3.1-8b-bnb-4bit", | |
| "architectures": [ | |
| "LlamaForCausalLM" | |
| ], | |
| "attention_bias": false, | |
| "attention_dropout": 0.0, | |
| "bos_token_id": 128000, | |
| "eos_token_id": 128001, | |
| "hidden_act": "silu", | |
| "hidden_size": 4096, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 14336, | |
| "max_position_embeddings": 131072, | |
| "mlp_bias": false, | |
| "model_type": "llama", | |
| "num_attention_heads": 32, | |
| "num_hidden_layers": 32, | |
| "num_key_value_heads": 8, | |
| "pad_token_id": 128004, | |
| "pretraining_tp": 1, | |
| "quantization_config": { | |
| "bnb_4bit_compute_dtype": "float16", | |
| "bnb_4bit_quant_type": "nf4", | |
| "bnb_4bit_use_double_quant": true, | |
| "llm_int8_enable_fp32_cpu_offload": false, | |
| "llm_int8_has_fp16_weight": false, | |
| "llm_int8_skip_modules": null, | |
| "llm_int8_threshold": 6.0, | |
| "load_in_4bit": true, | |
| "load_in_8bit": false, | |
| "quant_method": "bitsandbytes" | |
| }, | |
| "rms_norm_eps": 1e-05, | |
| "rope_scaling": { | |
| "factor": 8.0, | |
| "high_freq_factor": 4.0, | |
| "low_freq_factor": 1.0, | |
| "original_max_position_embeddings": 8192, | |
| "rope_type": "llama3" | |
| }, | |
| "rope_theta": 500000.0, | |
| "tie_word_embeddings": false, | |
| "torch_dtype": "float16", | |
| "transformers_version": "4.44.2", | |
| "unsloth_version": "2024.8", | |
| "use_cache": true, | |
| "vocab_size": 128256 | |
| } | |