Instructions to use KuldeepRawat64/hrms_trained with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KuldeepRawat64/hrms_trained with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("KuldeepRawat64/hrms_trained", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use KuldeepRawat64/hrms_trained 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 KuldeepRawat64/hrms_trained:Q8_0 # Run inference directly in the terminal: llama cli -hf KuldeepRawat64/hrms_trained:Q8_0
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf KuldeepRawat64/hrms_trained:Q8_0 # Run inference directly in the terminal: llama cli -hf KuldeepRawat64/hrms_trained:Q8_0
Build from source code
git clone https://github.com/ggml-org/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-app # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama serve -hf KuldeepRawat64/hrms_trained:Q8_0 # Run inference directly in the terminal: ./build/bin/llama cli -hf KuldeepRawat64/hrms_trained:Q8_0
Use Docker
docker model run hf.co/KuldeepRawat64/hrms_trained:Q8_0
- Llama new
- LM Studio
- Jan
- Ollama
How to use KuldeepRawat64/hrms_trained with Ollama:
ollama run hf.co/KuldeepRawat64/hrms_trained:Q8_0
- Unsloth Desktop
- Docker Model Runner
How to use KuldeepRawat64/hrms_trained with Docker Model Runner:
docker model run hf.co/KuldeepRawat64/hrms_trained:Q8_0
- Lemonade
How to use KuldeepRawat64/hrms_trained with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull KuldeepRawat64/hrms_trained:Q8_0
Run and chat with the model
lemonade run user.hrms_trained-Q8_0
List all available models
lemonade list
- Atomic Chat
File size: 513 Bytes
4bfbb34 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | FROM /content/KuldeepRawat64/hrms_trained/unsloth.Q8_0.gguf
TEMPLATE """Below are some instructions that describe some tasks. Write responses that appropriately complete each request.{{ if .Prompt }}
### Instruction:
{{ .Prompt }}{{ end }}
### Response:
{{ .Response }}<|end_of_text|>"""
PARAMETER stop "<|end_header_id|>"
PARAMETER stop "<|eot_id|>"
PARAMETER stop "<|start_header_id|>"
PARAMETER stop "<|end_of_text|>"
PARAMETER stop "<|reserved_special_token_"
PARAMETER temperature 1.5
PARAMETER min_p 0.1 |