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
| { | |
| "_attn_implementation_autoset": true, | |
| "_name_or_path": "internlm/internlm3-8b-instruct", | |
| "architectures": [ | |
| "InternLM3ForCausalLM" | |
| ], | |
| "attention_dropout": 0.0, | |
| "auto_map": { | |
| "AutoConfig": "internlm/internlm3-8b-instruct--configuration_internlm3.InternLM3Config", | |
| "AutoModel": "internlm/internlm3-8b-instruct--modeling_internlm3.InternLM3Model", | |
| "AutoModelForCausalLM": "internlm/internlm3-8b-instruct--modeling_internlm3.InternLM3ForCausalLM" | |
| }, | |
| "bias": false, | |
| "bos_token_id": 1, | |
| "eos_token_id": 2, | |
| "head_dim": 128, | |
| "hidden_act": "silu", | |
| "hidden_size": 4096, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 10240, | |
| "max_position_embeddings": 32768, | |
| "model_type": "internlm3", | |
| "num_attention_heads": 32, | |
| "num_hidden_layers": 48, | |
| "num_key_value_heads": 2, | |
| "pad_token_id": 2, | |
| "qkv_bias": false, | |
| "quantization_config": { | |
| "_load_in_4bit": true, | |
| "_load_in_8bit": false, | |
| "bnb_4bit_compute_dtype": "bfloat16", | |
| "bnb_4bit_quant_storage": "bfloat16", | |
| "bnb_4bit_quant_type": "nf4", | |
| "bnb_4bit_use_double_quant": true, | |
| "llm_int8_enable_fp32_cpu_offload": false, | |
| "llm_int8_has_fp16_weight": false, | |
| "llm_int8_skip_modules": null, | |
| "llm_int8_threshold": 6.0, | |
| "load_in_4bit": true, | |
| "load_in_8bit": false, | |
| "quant_method": "bitsandbytes" | |
| }, | |
| "rms_norm_eps": 1e-05, | |
| "rope_scaling": { | |
| "factor": 6.0, | |
| "rope_type": "dynamic" | |
| }, | |
| "rope_theta": 50000000, | |
| "tie_word_embeddings": false, | |
| "torch_dtype": "bfloat16", | |
| "transformers_version": "4.47.1", | |
| "use_cache": false, | |
| "vocab_size": 128133 | |
| } | |