Instructions to use SnehaPriyaaMP/FINAL_NEW_TEST with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use SnehaPriyaaMP/FINAL_NEW_TEST with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/llama-3-8b-bnb-4bit") model = PeftModel.from_pretrained(base_model, "SnehaPriyaaMP/FINAL_NEW_TEST") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use SnehaPriyaaMP/FINAL_NEW_TEST 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 SnehaPriyaaMP/FINAL_NEW_TEST:Q6_K # Run inference directly in the terminal: llama cli -hf SnehaPriyaaMP/FINAL_NEW_TEST:Q6_K
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf SnehaPriyaaMP/FINAL_NEW_TEST:Q6_K # Run inference directly in the terminal: llama cli -hf SnehaPriyaaMP/FINAL_NEW_TEST:Q6_K
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 SnehaPriyaaMP/FINAL_NEW_TEST:Q6_K # Run inference directly in the terminal: ./llama-cli -hf SnehaPriyaaMP/FINAL_NEW_TEST:Q6_K
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 SnehaPriyaaMP/FINAL_NEW_TEST:Q6_K # Run inference directly in the terminal: ./build/bin/llama-cli -hf SnehaPriyaaMP/FINAL_NEW_TEST:Q6_K
Use Docker
docker model run hf.co/SnehaPriyaaMP/FINAL_NEW_TEST:Q6_K
- Llama new
- LM Studio
- Jan
- Ollama
How to use SnehaPriyaaMP/FINAL_NEW_TEST with Ollama:
ollama run hf.co/SnehaPriyaaMP/FINAL_NEW_TEST:Q6_K
- Unsloth Desktop
- Docker Model Runner
How to use SnehaPriyaaMP/FINAL_NEW_TEST with Docker Model Runner:
docker model run hf.co/SnehaPriyaaMP/FINAL_NEW_TEST:Q6_K
- Lemonade
How to use SnehaPriyaaMP/FINAL_NEW_TEST with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull SnehaPriyaaMP/FINAL_NEW_TEST:Q6_K
Run and chat with the model
lemonade run user.FINAL_NEW_TEST-Q6_K
List all available models
lemonade list
- Atomic Chat
Download tokenizer.json from SnehaPriyaaMP/FINAL_NEW_TEST: direct link, hf CLI and curl.
- Browser
- Download file 17.2 MB
-
https://huggingface.co/SnehaPriyaaMP/FINAL_NEW_TEST/resolve/main/tokenizer.json
- Command line
-
hf download hf://SnehaPriyaaMP/FINAL_NEW_TEST/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/SnehaPriyaaMP/FINAL_NEW_TEST/resolve/main/tokenizer.json
17.2 MB
- Xet hash:
- f50a225d9f53b6d10de736023ad24fa9ce92634801004eb39d881f415a4784cb
- Size of remote file:
- 17.2 MB
- SHA256:
- 3c5cf44023714fb39b05e71e425f8d7b92805ff73f7988b083b8c87f0bf87393
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