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#1
by schroneko - opened
README.md ADDED
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+ ---
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+ language:
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+ - ja
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+ - en
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+ license: other
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+ license_link: LICENSE
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+ tags:
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+ - mlx
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+ base_model: sbintuitions/sarashina2.1-1b
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+ ---
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+
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+ # mlx-community/sarashina2.1-1b-8bit
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+
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+ The Model [mlx-community/sarashina2.1-1b-8bit](https://huggingface.co/mlx-community/sarashina2.1-1b-8bit) was
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+ converted to MLX format from [sbintuitions/sarashina2.1-1b](https://huggingface.co/sbintuitions/sarashina2.1-1b)
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+ using mlx-lm version **0.20.2**.
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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/sarashina2.1-1b-8bit")
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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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+ "max_position_embeddings": 8192,
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+ "mlp_bias": false,
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+ "num_attention_heads": 16,
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+ "num_hidden_layers": 24,
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+ "num_key_value_heads": 8,
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+ "pretraining_tp": 1,
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+ "quantization": {
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+ "group_size": 64,
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+ "bits": 8
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+ },
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+ "quantization_config": {
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+ "group_size": 64,
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+ "bits": 8
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+ },
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+ "rms_norm_eps": 1e-05,
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+ "rope_scaling": null,
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+ "rope_theta": 500000,
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+ "tie_word_embeddings": false,
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+ "torch_dtype": "bfloat16",
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+ "transformers_version": "4.40.1",
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+ "use_cache": true,
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+ "vocab_size": 102400
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+ }
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