Transformers
Safetensors
GGUF
English
mistral
text-generation-inference
unsloth
trl
sft
conversational
Instructions to use AlSamCur123/NemoUnslothExpimentalSettings with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AlSamCur123/NemoUnslothExpimentalSettings with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("AlSamCur123/NemoUnslothExpimentalSettings", dtype="auto") - llama-cpp-python
How to use AlSamCur123/NemoUnslothExpimentalSettings with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="AlSamCur123/NemoUnslothExpimentalSettings", filename="NemoUnslothExpimentalSettings.Q4_0.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 AlSamCur123/NemoUnslothExpimentalSettings with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf AlSamCur123/NemoUnslothExpimentalSettings:Q4_K_M # Run inference directly in the terminal: llama-cli -hf AlSamCur123/NemoUnslothExpimentalSettings:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf AlSamCur123/NemoUnslothExpimentalSettings:Q4_K_M # Run inference directly in the terminal: llama-cli -hf AlSamCur123/NemoUnslothExpimentalSettings:Q4_K_M
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 AlSamCur123/NemoUnslothExpimentalSettings:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf AlSamCur123/NemoUnslothExpimentalSettings:Q4_K_M
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 AlSamCur123/NemoUnslothExpimentalSettings:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf AlSamCur123/NemoUnslothExpimentalSettings:Q4_K_M
Use Docker
docker model run hf.co/AlSamCur123/NemoUnslothExpimentalSettings:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use AlSamCur123/NemoUnslothExpimentalSettings with Ollama:
ollama run hf.co/AlSamCur123/NemoUnslothExpimentalSettings:Q4_K_M
- Unsloth Studio new
How to use AlSamCur123/NemoUnslothExpimentalSettings 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 AlSamCur123/NemoUnslothExpimentalSettings 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 AlSamCur123/NemoUnslothExpimentalSettings to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for AlSamCur123/NemoUnslothExpimentalSettings to start chatting
- Docker Model Runner
How to use AlSamCur123/NemoUnslothExpimentalSettings with Docker Model Runner:
docker model run hf.co/AlSamCur123/NemoUnslothExpimentalSettings:Q4_K_M
- Lemonade
How to use AlSamCur123/NemoUnslothExpimentalSettings with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull AlSamCur123/NemoUnslothExpimentalSettings:Q4_K_M
Run and chat with the model
lemonade run user.NemoUnslothExpimentalSettings-Q4_K_M
List all available models
lemonade list
Upload tokenizer
Browse files- .gitattributes +1 -0
- special_tokens_map.json +30 -0
- tokenizer.json +3 -0
- tokenizer_config.json +0 -0
.gitattributes
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special_tokens_map.json
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{
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"bos_token": {
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"lstrip": false,
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"normalized": false,
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version https://git-lfs.github.com/spec/v1
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oid sha256:b0240ce510f08e6c2041724e9043e33be9d251d1e4a4d94eb68cd47b954b61d2
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size 17078292
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tokenizer_config.json
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