Instructions to use codesbyusman/codellama7bvulnerabilitymitigator with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use codesbyusman/codellama7bvulnerabilitymitigator with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("codesbyusman/codellama7bvulnerabilitymitigator", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use codesbyusman/codellama7bvulnerabilitymitigator with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for codesbyusman/codellama7bvulnerabilitymitigator to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for codesbyusman/codellama7bvulnerabilitymitigator to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for codesbyusman/codellama7bvulnerabilitymitigator to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="codesbyusman/codellama7bvulnerabilitymitigator", max_seq_length=2048, )
| { | |
| "_name_or_path": "codesbyusman/codellama7bvulnerabilitymitigator", | |
| "alpha_pattern": {}, | |
| "attention_bias": false, | |
| "attention_dropout": 0.0, | |
| "auto_mapping": null, | |
| "base_model_name_or_path": "unsloth/codellama-7b-bnb-4bit", | |
| "bias": "none", | |
| "bos_token_id": 1, | |
| "eos_token_id": 2, | |
| "fan_in_fan_out": false, | |
| "hidden_act": "silu", | |
| "hidden_size": 4096, | |
| "inference_mode": true, | |
| "init_lora_weights": true, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 11008, | |
| "layer_replication": null, | |
| "layers_pattern": null, | |
| "layers_to_transform": null, | |
| "loftq_config": {}, | |
| "lora_alpha": 16, | |
| "lora_dropout": 0, | |
| "max_position_embeddings": 2048, | |
| "megatron_config": null, | |
| "megatron_core": "megatron.core", | |
| "model_type": "llama", | |
| "modules_to_save": null, | |
| "num_attention_heads": 32, | |
| "num_hidden_layers": 32, | |
| "num_key_value_heads": 32, | |
| "peft_type": "LORA", | |
| "pretraining_tp": 1, | |
| "r": 16, | |
| "rank_pattern": {}, | |
| "revision": "unsloth", | |
| "rms_norm_eps": 1e-06, | |
| "rope_scaling": null, | |
| "rope_theta": 10000.0, | |
| "target_modules": [ | |
| "k_proj", | |
| "down_proj", | |
| "v_proj", | |
| "gate_proj", | |
| "q_proj", | |
| "up_proj", | |
| "o_proj" | |
| ], | |
| "task_type": "CAUSAL_LM", | |
| "tie_word_embeddings": false, | |
| "transformers_version": "4.40.1", | |
| "use_cache": true, | |
| "use_dora": false, | |
| "use_rslora": false, | |
| "vocab_size": 32000 | |
| } | |