Instructions to use jeiku/Everything_v3_128_StableLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use jeiku/Everything_v3_128_StableLM with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("stabilityai/stablelm-3b-4e1t") model = PeftModel.from_pretrained(base_model, "jeiku/Everything_v3_128_StableLM") - Notebooks
- Google Colab
- Kaggle
| { | |
| "_name_or_path": "stabilityai/stablelm-3b-4e1t", | |
| "architectures": [ | |
| "StableLMEpochForCausalLM" | |
| ], | |
| "auto_map": { | |
| "AutoConfig": "configuration_stablelm_epoch.StableLMEpochConfig", | |
| "AutoModelForCausalLM": "stabilityai/stablelm-3b-4e1t--modeling_stablelm_epoch.StableLMEpochForCausalLM" | |
| }, | |
| "bos_token_id": 0, | |
| "eos_token_id": 0, | |
| "hidden_act": "silu", | |
| "hidden_size": 2560, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 6912, | |
| "max_position_embeddings": 4096, | |
| "model_type": "stablelm_epoch", | |
| "norm_eps": 1e-05, | |
| "num_attention_heads": 32, | |
| "num_heads": 32, | |
| "num_hidden_layers": 32, | |
| "num_key_value_heads": 32, | |
| "quantization_config": { | |
| "bnb_4bit_compute_dtype": "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" | |
| }, | |
| "rope_pct": 0.25, | |
| "rope_theta": 10000, | |
| "rotary_scaling_factor": 1.0, | |
| "tie_word_embeddings": false, | |
| "torch_dtype": "bfloat16", | |
| "transformers_version": "4.37.0.dev0", | |
| "use_cache": false, | |
| "vocab_size": 50304 | |
| } | |