Text Generation
Transformers
Safetensors
GGUF
English
llama
text-generation-inference
unsloth
trl
sft
4-bit precision
bitsandbytes
Instructions to use simpsonhuang/llama-fintune with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use simpsonhuang/llama-fintune with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="simpsonhuang/llama-fintune")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("simpsonhuang/llama-fintune") model = AutoModelForCausalLM.from_pretrained("simpsonhuang/llama-fintune", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use simpsonhuang/llama-fintune 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 simpsonhuang/llama-fintune:F16 # Run inference directly in the terminal: llama cli -hf simpsonhuang/llama-fintune:F16
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf simpsonhuang/llama-fintune:F16 # Run inference directly in the terminal: llama cli -hf simpsonhuang/llama-fintune:F16
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 simpsonhuang/llama-fintune:F16 # Run inference directly in the terminal: ./llama-cli -hf simpsonhuang/llama-fintune:F16
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 simpsonhuang/llama-fintune:F16 # Run inference directly in the terminal: ./build/bin/llama-cli -hf simpsonhuang/llama-fintune:F16
Use Docker
docker model run hf.co/simpsonhuang/llama-fintune:F16
- LM Studio
- Jan
- vLLM
How to use simpsonhuang/llama-fintune with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "simpsonhuang/llama-fintune" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "simpsonhuang/llama-fintune", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/simpsonhuang/llama-fintune:F16
- SGLang
How to use simpsonhuang/llama-fintune 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 "simpsonhuang/llama-fintune" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "simpsonhuang/llama-fintune", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'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 "simpsonhuang/llama-fintune" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "simpsonhuang/llama-fintune", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Ollama
How to use simpsonhuang/llama-fintune with Ollama:
ollama run hf.co/simpsonhuang/llama-fintune:F16
- Unsloth Desktop
- Docker Model Runner
How to use simpsonhuang/llama-fintune with Docker Model Runner:
docker model run hf.co/simpsonhuang/llama-fintune:F16
- Lemonade
How to use simpsonhuang/llama-fintune with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull simpsonhuang/llama-fintune:F16
Run and chat with the model
lemonade run user.llama-fintune-F16
List all available models
lemonade list
- Atomic Chat
Trained with Unsloth
Browse filesUpload model trained with Unsloth 2x faster
- README.md +1 -0
- config.json +48 -2
- generation_config.json +11 -0
- model-00001-of-00002.safetensors +3 -0
- model-00002-of-00002.safetensors +3 -0
- model.safetensors.index.json +0 -0
README.md
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- unsloth
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- llama
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- trl
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---
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# Uploaded model
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- unsloth
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- llama
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- trl
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- sft
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---
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# Uploaded model
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config.json
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{
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{
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"_name_or_path": "unsloth/meta-llama-3.1-8b-bnb-4bit",
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"architectures": [
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"LlamaForCausalLM"
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],
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"attention_bias": false,
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"attention_dropout": 0.0,
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"bos_token_id": 128000,
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"eos_token_id": 128001,
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"hidden_act": "silu",
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"hidden_size": 4096,
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"initializer_range": 0.02,
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"intermediate_size": 14336,
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"max_position_embeddings": 131072,
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"mlp_bias": false,
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"model_type": "llama",
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"num_attention_heads": 32,
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"num_hidden_layers": 32,
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"num_key_value_heads": 8,
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"pad_token_id": 128004,
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"pretraining_tp": 1,
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"quantization_config": {
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"bnb_4bit_compute_dtype": "float16",
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"bnb_4bit_quant_type": "nf4",
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"bnb_4bit_use_double_quant": true,
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"llm_int8_enable_fp32_cpu_offload": false,
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"llm_int8_has_fp16_weight": false,
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"llm_int8_skip_modules": null,
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"llm_int8_threshold": 6.0,
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"load_in_4bit": true,
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"load_in_8bit": false,
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"quant_method": "bitsandbytes"
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},
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"rms_norm_eps": 1e-05,
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"rope_scaling": {
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"factor": 8.0,
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"high_freq_factor": 4.0,
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"low_freq_factor": 1.0,
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"original_max_position_embeddings": 8192,
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"rope_type": "llama3"
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},
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"rope_theta": 500000.0,
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"tie_word_embeddings": false,
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"torch_dtype": "float16",
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"transformers_version": "4.44.2",
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"unsloth_version": "2024.8",
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"use_cache": true,
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"vocab_size": 128256
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}
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generation_config.json
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{
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"_from_model_config": true,
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"bos_token_id": 128000,
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"do_sample": true,
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"eos_token_id": 128001,
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"max_length": 131072,
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"pad_token_id": 128004,
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"temperature": 0.6,
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"top_p": 0.9,
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"transformers_version": "4.44.2"
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}
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model-00001-of-00002.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:7fbb7f87a9548f0be2aa58b7c4dd2fe6c8e86818542ae1ca5fa9d633166710f3
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size 4652072860
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model-00002-of-00002.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:2b9f8fb3a26772f655e8508705dc914ca71e511cdb96ac35b11daa6958e64dc1
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size 1050673280
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model.safetensors.index.json
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