Instructions to use TheWirelessPhoenix/mistral-7b-oQ4e with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use TheWirelessPhoenix/mistral-7b-oQ4e with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir mistral-7b-oQ4e TheWirelessPhoenix/mistral-7b-oQ4e
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
| { | |
| "_name_or_path": "unsloth/mistral-7b", | |
| "architectures": [ | |
| "MistralForCausalLM" | |
| ], | |
| "attention_dropout": 0.0, | |
| "bos_token_id": 1, | |
| "eos_token_id": 2, | |
| "head_dim": 128, | |
| "hidden_act": "silu", | |
| "hidden_size": 4096, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 14336, | |
| "max_position_embeddings": 32768, | |
| "model_type": "mistral", | |
| "num_attention_heads": 32, | |
| "num_hidden_layers": 32, | |
| "num_key_value_heads": 8, | |
| "pad_token_id": 0, | |
| "rms_norm_eps": 1e-05, | |
| "rope_theta": 10000.0, | |
| "sliding_window": 4096, | |
| "tie_word_embeddings": false, | |
| "torch_dtype": "bfloat16", | |
| "transformers_version": "4.44.2", | |
| "unsloth_version": "2024.9", | |
| "use_cache": true, | |
| "vocab_size": 32000, | |
| "quantization": { | |
| "group_size": 64, | |
| "bits": 4, | |
| "mode": "affine", | |
| "model.embed_tokens": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.0.mlp.down_proj": { | |
| "bits": 6, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.0.self_attn.k_proj": { | |
| "bits": 5, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.0.self_attn.o_proj": { | |
| "bits": 5, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.0.self_attn.q_proj": { | |
| "bits": 5, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.0.self_attn.v_proj": { | |
| "bits": 6, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.1.mlp.down_proj": { | |
| "bits": 6, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.1.self_attn.k_proj": { | |
| "bits": 5, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.1.self_attn.o_proj": { | |
| "bits": 5, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.1.self_attn.q_proj": { | |
| "bits": 5, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.1.self_attn.v_proj": { | |
| "bits": 6, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.10.self_attn.o_proj": { | |
| "bits": 5, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.2.self_attn.o_proj": { | |
| "bits": 5, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.3.self_attn.o_proj": { | |
| "bits": 5, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.4.self_attn.o_proj": { | |
| "bits": 5, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "lm_head": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.26.self_attn.k_proj": { | |
| "bits": 5, | |
| "group_size": 64, | |
| "mode": "affine" | |
| } | |
| }, | |
| "quantization_config": { | |
| "group_size": 64, | |
| "bits": 4, | |
| "mode": "affine", | |
| "model.embed_tokens": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.0.mlp.down_proj": { | |
| "bits": 6, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.0.self_attn.k_proj": { | |
| "bits": 5, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.0.self_attn.o_proj": { | |
| "bits": 5, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.0.self_attn.q_proj": { | |
| "bits": 5, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.0.self_attn.v_proj": { | |
| "bits": 6, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.1.mlp.down_proj": { | |
| "bits": 6, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.1.self_attn.k_proj": { | |
| "bits": 5, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.1.self_attn.o_proj": { | |
| "bits": 5, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.1.self_attn.q_proj": { | |
| "bits": 5, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.1.self_attn.v_proj": { | |
| "bits": 6, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.10.self_attn.o_proj": { | |
| "bits": 5, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.2.self_attn.o_proj": { | |
| "bits": 5, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.3.self_attn.o_proj": { | |
| "bits": 5, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.4.self_attn.o_proj": { | |
| "bits": 5, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "lm_head": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.26.self_attn.k_proj": { | |
| "bits": 5, | |
| "group_size": 64, | |
| "mode": "affine" | |
| } | |
| } | |
| } |