PEFT
Safetensors
GGUF
internlm3
axolotl
Generated from Trainer
custom_code
4-bit precision
bitsandbytes
conversational
Instructions to use ToastyPigeon/intern-rp-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use ToastyPigeon/intern-rp-lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("internlm/internlm3-8b-instruct") model = PeftModel.from_pretrained(base_model, "ToastyPigeon/intern-rp-lora") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use ToastyPigeon/intern-rp-lora 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 ToastyPigeon/intern-rp-lora:Q8_0 # Run inference directly in the terminal: llama cli -hf ToastyPigeon/intern-rp-lora:Q8_0
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf ToastyPigeon/intern-rp-lora:Q8_0 # Run inference directly in the terminal: llama cli -hf ToastyPigeon/intern-rp-lora:Q8_0
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 ToastyPigeon/intern-rp-lora:Q8_0 # Run inference directly in the terminal: ./llama-cli -hf ToastyPigeon/intern-rp-lora:Q8_0
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 ToastyPigeon/intern-rp-lora:Q8_0 # Run inference directly in the terminal: ./build/bin/llama-cli -hf ToastyPigeon/intern-rp-lora:Q8_0
Use Docker
docker model run hf.co/ToastyPigeon/intern-rp-lora:Q8_0
- LM Studio
- Jan
- Ollama
How to use ToastyPigeon/intern-rp-lora with Ollama:
ollama run hf.co/ToastyPigeon/intern-rp-lora:Q8_0
- Unsloth Desktop
- Docker Model Runner
How to use ToastyPigeon/intern-rp-lora with Docker Model Runner:
docker model run hf.co/ToastyPigeon/intern-rp-lora:Q8_0
- Lemonade
How to use ToastyPigeon/intern-rp-lora with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull ToastyPigeon/intern-rp-lora:Q8_0
Run and chat with the model
lemonade run user.intern-rp-lora-Q8_0
List all available models
lemonade list
- Atomic Chat
| { | |
| "alpha_pattern": {}, | |
| "auto_mapping": null, | |
| "base_model_name_or_path": "internlm/internlm3-8b-instruct", | |
| "bias": "none", | |
| "eva_config": null, | |
| "exclude_modules": null, | |
| "fan_in_fan_out": null, | |
| "inference_mode": true, | |
| "init_lora_weights": true, | |
| "layer_replication": null, | |
| "layers_pattern": null, | |
| "layers_to_transform": null, | |
| "loftq_config": {}, | |
| "lora_alpha": 64, | |
| "lora_bias": false, | |
| "lora_dropout": 0.25, | |
| "megatron_config": null, | |
| "megatron_core": "megatron.core", | |
| "modules_to_save": null, | |
| "peft_type": "LORA", | |
| "r": 32, | |
| "rank_pattern": {}, | |
| "revision": null, | |
| "target_modules": [ | |
| "v_proj", | |
| "gate_proj", | |
| "down_proj", | |
| "k_proj", | |
| "o_proj", | |
| "q_proj", | |
| "up_proj" | |
| ], | |
| "task_type": "CAUSAL_LM", | |
| "use_dora": false, | |
| "use_rslora": false | |
| } |