Question Answering
Transformers
Safetensors
GGUF
English
llama
text-generation-inference
unsloth
trl
Instructions to use ayushrupapara/llama3_8b_flanv2_cot with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ayushrupapara/llama3_8b_flanv2_cot with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="ayushrupapara/llama3_8b_flanv2_cot")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ayushrupapara/llama3_8b_flanv2_cot", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use ayushrupapara/llama3_8b_flanv2_cot 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 ayushrupapara/llama3_8b_flanv2_cot:Q4_K_M # Run inference directly in the terminal: llama cli -hf ayushrupapara/llama3_8b_flanv2_cot:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf ayushrupapara/llama3_8b_flanv2_cot:Q4_K_M # Run inference directly in the terminal: llama cli -hf ayushrupapara/llama3_8b_flanv2_cot: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 ayushrupapara/llama3_8b_flanv2_cot:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf ayushrupapara/llama3_8b_flanv2_cot: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 ayushrupapara/llama3_8b_flanv2_cot:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf ayushrupapara/llama3_8b_flanv2_cot:Q4_K_M
Use Docker
docker model run hf.co/ayushrupapara/llama3_8b_flanv2_cot:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use ayushrupapara/llama3_8b_flanv2_cot with Ollama:
ollama run hf.co/ayushrupapara/llama3_8b_flanv2_cot:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use ayushrupapara/llama3_8b_flanv2_cot with Docker Model Runner:
docker model run hf.co/ayushrupapara/llama3_8b_flanv2_cot:Q4_K_M
- Lemonade
How to use ayushrupapara/llama3_8b_flanv2_cot with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull ayushrupapara/llama3_8b_flanv2_cot:Q4_K_M
Run and chat with the model
lemonade run user.llama3_8b_flanv2_cot-Q4_K_M
List all available models
lemonade list
- Atomic Chat
Download special_tokens_map.json from ayushrupapara/llama3_8b_flanv2_cot: direct link, hf CLI and curl.
- Browser
- Download file 464 Bytes
-
https://huggingface.co/ayushrupapara/llama3_8b_flanv2_cot/resolve/7a94bfa395253cb4b7e737662a5ed1b4df77f21e/special_tokens_map.json
- Command line
-
hf download hf://ayushrupapara/llama3_8b_flanv2_cot@7a94bfa395253cb4b7e737662a5ed1b4df77f21e/special_tokens_map.json
-
curl -L -o special_tokens_map.json https://huggingface.co/ayushrupapara/llama3_8b_flanv2_cot/resolve/7a94bfa395253cb4b7e737662a5ed1b4df77f21e/special_tokens_map.json
464 Bytes
| { | |
| "bos_token": { | |
| "content": "<|begin_of_text|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false | |
| }, | |
| "eos_token": { | |
| "content": "<|end_of_text|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false | |
| }, | |
| "pad_token": { | |
| "content": "<|reserved_special_token_250|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false | |
| } | |
| } | |