Reinforcement Learning
Transformers
GGUF
Chinese
English
incremental-pretraining
sft
roleplay
cot
sex
conversational
Not-For-All-Audiences
Instructions to use ValueFX9507/Tifa-Deepsex-14b-CoT-GGUF-Q4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ValueFX9507/Tifa-Deepsex-14b-CoT-GGUF-Q4 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ValueFX9507/Tifa-Deepsex-14b-CoT-GGUF-Q4", dtype="auto") - llama-cpp-python
How to use ValueFX9507/Tifa-Deepsex-14b-CoT-GGUF-Q4 with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="ValueFX9507/Tifa-Deepsex-14b-CoT-GGUF-Q4", filename="Tifa-Deepsex-14b-CoT-Chat-IQ4_NL.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use ValueFX9507/Tifa-Deepsex-14b-CoT-GGUF-Q4 with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf ValueFX9507/Tifa-Deepsex-14b-CoT-GGUF-Q4:IQ4_NL # Run inference directly in the terminal: llama-cli -hf ValueFX9507/Tifa-Deepsex-14b-CoT-GGUF-Q4:IQ4_NL
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf ValueFX9507/Tifa-Deepsex-14b-CoT-GGUF-Q4:IQ4_NL # Run inference directly in the terminal: llama-cli -hf ValueFX9507/Tifa-Deepsex-14b-CoT-GGUF-Q4:IQ4_NL
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 ValueFX9507/Tifa-Deepsex-14b-CoT-GGUF-Q4:IQ4_NL # Run inference directly in the terminal: ./llama-cli -hf ValueFX9507/Tifa-Deepsex-14b-CoT-GGUF-Q4:IQ4_NL
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 ValueFX9507/Tifa-Deepsex-14b-CoT-GGUF-Q4:IQ4_NL # Run inference directly in the terminal: ./build/bin/llama-cli -hf ValueFX9507/Tifa-Deepsex-14b-CoT-GGUF-Q4:IQ4_NL
Use Docker
docker model run hf.co/ValueFX9507/Tifa-Deepsex-14b-CoT-GGUF-Q4:IQ4_NL
- LM Studio
- Jan
- Ollama
How to use ValueFX9507/Tifa-Deepsex-14b-CoT-GGUF-Q4 with Ollama:
ollama run hf.co/ValueFX9507/Tifa-Deepsex-14b-CoT-GGUF-Q4:IQ4_NL
- Unsloth Studio
How to use ValueFX9507/Tifa-Deepsex-14b-CoT-GGUF-Q4 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 ValueFX9507/Tifa-Deepsex-14b-CoT-GGUF-Q4 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 ValueFX9507/Tifa-Deepsex-14b-CoT-GGUF-Q4 to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for ValueFX9507/Tifa-Deepsex-14b-CoT-GGUF-Q4 to start chatting
- Atomic Chat new
- Docker Model Runner
How to use ValueFX9507/Tifa-Deepsex-14b-CoT-GGUF-Q4 with Docker Model Runner:
docker model run hf.co/ValueFX9507/Tifa-Deepsex-14b-CoT-GGUF-Q4:IQ4_NL
- Lemonade
How to use ValueFX9507/Tifa-Deepsex-14b-CoT-GGUF-Q4 with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull ValueFX9507/Tifa-Deepsex-14b-CoT-GGUF-Q4:IQ4_NL
Run and chat with the model
lemonade run user.Tifa-Deepsex-14b-CoT-GGUF-Q4-IQ4_NL
List all available models
lemonade list
File size: 652 Bytes
f4560cf | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 | FROM D:/llamacpp/llama.cpp/models/Tifa-Deepsex-14b-CoT-Q4_K_M.gguf
TEMPLATE """
{{- if .System }}{{ .System }}{{ end }}
{{- range $i, $_ := .Messages }}
{{- $last := eq (len (slice $.Messages $i)) 1}}
{{- if eq .Role "user" }}<|User|>{{ .Content }}
{{- else if eq .Role "assistant" }}<|Assistant|>{{ .Content }}{{- if not $last }}<|end▁of▁sentence|>{{- end }}
{{- end }}
{{- if and $last (ne .Role "assistant") }}<|Assistant|>{{- end }}
{{- end }}"""
PARAMETER stop "<|begin▁of▁sentence|>"
PARAMETER stop "<|end▁of▁sentence|>"
PARAMETER stop "<|User|>"
PARAMETER stop "<|Assistant|>" |