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README.md ADDED
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+ ---
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+ license: other
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+ license_name: mrl
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+ language:
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+ - en
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+ tags:
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+ - chat
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+ - mlx
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+ pipeline_tag: text-generation
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+ library_name: transformers
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+ datasets:
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+ - anthracite-org/c2_logs_16k_mistral-large_v1.2
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+ - anthracite-org/kalo-opus-instruct-22k-no-refusal
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+ - lodrick-the-lafted/kalo-opus-instruct-3k-filtered
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+ - anthracite-org/nopm_claude_writing_fixed
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+ - anthracite-org/kalo_opus_misc_240827
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+ - anthracite-org/kalo_misc_part2
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+ base_model: anthracite-org/magnum-v4-123b
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+ ---
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+
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+ # mlx-community/magnum-v4-123b-4bit
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+
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+ The Model [mlx-community/magnum-v4-123b-4bit](https://huggingface.co/mlx-community/magnum-v4-123b-4bit) was
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+ converted to MLX format from [anthracite-org/magnum-v4-123b](https://huggingface.co/anthracite-org/magnum-v4-123b)
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+ using mlx-lm version **0.20.4**.
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+
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+ ## Use with mlx
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+
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+ ```bash
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+ pip install mlx-lm
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+ ```
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+
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+ ```python
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+ from mlx_lm import load, generate
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+
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+ model, tokenizer = load("mlx-community/magnum-v4-123b-4bit")
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+
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+ prompt="hello"
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+
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+ if hasattr(tokenizer, "apply_chat_template") and 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, tokenize=False, add_generation_prompt=True
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+ )
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+
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+ response = generate(model, tokenizer, prompt=prompt, verbose=True)
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+ ```
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+ {
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+ "architectures": [
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+ "MistralForCausalLM"
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+ ],
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+ "attention_dropout": 0.0,
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+ "head_dim": 128,
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+ "hidden_act": "silu",
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+ "hidden_size": 12288,
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+ "initializer_range": 0.02,
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+ "intermediate_size": 28672,
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+ "max_position_embeddings": 131072,
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+ "model_type": "mistral",
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+ "num_attention_heads": 96,
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+ "num_hidden_layers": 88,
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+ "num_key_value_heads": 8,
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+ "quantization": {
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+ "group_size": 64,
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+ "bits": 4
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+ },
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+ "quantization_config": {
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+ },
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+ "rms_norm_eps": 1e-05,
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+ "rope_theta": 1000000.0,
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+ "sliding_window": null,
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+ "tie_word_embeddings": false,
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+ "torch_dtype": "bfloat16",
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+ "transformers_version": "4.45.0.dev0",
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+ "use_cache": false,
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+ "vocab_size": 32768
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+ }
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