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- README.md +33 -0
- config.json +69 -0
- model-00001-of-00070.safetensors +3 -0
- model-00002-of-00070.safetensors +3 -0
- model-00003-of-00070.safetensors +3 -0
- model-00004-of-00070.safetensors +3 -0
- model-00005-of-00070.safetensors +3 -0
- model-00006-of-00070.safetensors +3 -0
- model-00007-of-00070.safetensors +3 -0
- model-00008-of-00070.safetensors +3 -0
- model-00009-of-00070.safetensors +3 -0
- model-00010-of-00070.safetensors +3 -0
- model-00011-of-00070.safetensors +3 -0
- model-00012-of-00070.safetensors +3 -0
- model-00013-of-00070.safetensors +3 -0
- model-00014-of-00070.safetensors +3 -0
- model-00015-of-00070.safetensors +3 -0
- model-00016-of-00070.safetensors +3 -0
- model-00017-of-00070.safetensors +3 -0
- model-00018-of-00070.safetensors +3 -0
- model-00019-of-00070.safetensors +3 -0
- model-00020-of-00070.safetensors +3 -0
- model-00021-of-00070.safetensors +3 -0
- model-00022-of-00070.safetensors +3 -0
- model-00023-of-00070.safetensors +3 -0
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- model-00025-of-00070.safetensors +3 -0
- model-00026-of-00070.safetensors +3 -0
- model-00027-of-00070.safetensors +3 -0
- model-00028-of-00070.safetensors +3 -0
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README.md
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---
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base_model: deepseek-ai/DeepSeek-V3
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tags:
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- mlx
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---
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# mlx-community/DeepSeek-V3-3bit
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The Model [mlx-community/DeepSeek-V3-3bit](https://huggingface.co/mlx-community/DeepSeek-V3-3bit) was
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converted to MLX format from [deepseek-ai/DeepSeek-V3](https://huggingface.co/deepseek-ai/DeepSeek-V3)
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using mlx-lm version **0.20.4**.
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## Use with mlx
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```bash
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pip install mlx-lm
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```
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```python
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from mlx_lm import load, generate
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model, tokenizer = load("mlx-community/DeepSeek-V3-3bit")
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prompt="hello"
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if tokenizer.chat_template is not None:
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messages = [{"role": "user", "content": prompt}]
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prompt = tokenizer.apply_chat_template(
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messages, add_generation_prompt=True
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)
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response = generate(model, tokenizer, prompt=prompt, verbose=True)
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```
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config.json
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{
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"architectures": [
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"DeepseekV3ForCausalLM"
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],
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"attention_bias": false,
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"attention_dropout": 0.0,
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"auto_map": {
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"AutoConfig": "configuration_deepseek.DeepseekV3Config",
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"AutoModel": "modeling_deepseek.DeepseekV3Model",
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"AutoModelForCausalLM": "modeling_deepseek.DeepseekV3ForCausalLM"
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},
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"aux_loss_alpha": 0.001,
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"bos_token_id": 0,
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"eos_token_id": 1,
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"ep_size": 1,
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"first_k_dense_replace": 3,
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"hidden_act": "silu",
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"hidden_size": 7168,
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"initializer_range": 0.02,
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"intermediate_size": 18432,
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"kv_lora_rank": 512,
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"max_position_embeddings": 163840,
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"model_type": "deepseek_v3",
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"moe_intermediate_size": 2048,
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"moe_layer_freq": 1,
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"n_group": 8,
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"n_routed_experts": 256,
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"n_shared_experts": 1,
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"norm_topk_prob": true,
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"num_attention_heads": 128,
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"num_experts_per_tok": 8,
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"num_hidden_layers": 61,
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"num_key_value_heads": 128,
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"num_nextn_predict_layers": 1,
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"pretraining_tp": 1,
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"q_lora_rank": 1536,
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"qk_nope_head_dim": 128,
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"qk_rope_head_dim": 64,
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"quantization": {
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"group_size": 32,
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"bits": 3
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},
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"quantization_config": {
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"group_size": 32,
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"bits": 3
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},
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"rms_norm_eps": 1e-06,
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"rope_scaling": {
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"beta_fast": 32,
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"beta_slow": 1,
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"factor": 40,
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"mscale": 1.0,
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"mscale_all_dim": 1.0,
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"original_max_position_embeddings": 4096,
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"type": "yarn"
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},
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"rope_theta": 10000,
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"routed_scaling_factor": 2.5,
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"scoring_func": "sigmoid",
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"seq_aux": true,
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"tie_word_embeddings": false,
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"topk_group": 4,
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"topk_method": "noaux_tc",
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"torch_dtype": "bfloat16",
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"transformers_version": "4.33.1",
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"use_cache": true,
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"v_head_dim": 128,
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"vocab_size": 129280
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}
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