初始化项目，由ModelHub XC社区提供模型

Model: ethicalabs/Tower-Plus-2B-mlx
Source: Original Platform

.gitattributes

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README.md

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+---
+base_model: Unbabel/Tower-Plus-2B
+license: cc-by-nc-sa-4.0
+language:
+- de
+- nl
+- is
+- es
+- fr
+- pt
+- uk
+- hi
+- zh
+- ru
+- cs
+- ko
+- ja
+- it
+- en
+- da
+- pl
+- hu
+- sv
+- 'no'
+- ro
+- fi
+library_name: mlx
+pipeline_tag: text-generation
+tags:
+- mlx
+---
+
+# ethicalabs/Tower-Plus-2B-mlx
+
+> [!WARNING]
+> This repository contains experimental models designed strictly for academic evaluation and research purposes.
+> 
+> Critical Constraints:
+> * **No Production Deployment:** Experimental models must not be deployed in commercial, enterprise, or mission-critical environments under any circumstances. 
+> * **No Liability:** Experimental models are provided "as-is" without warranties of any kind. The developers assume zero liability for downstream consequences, system integration failures, or regulatory non-compliance resulting from unauthorized deployment.
+
+This model [ethicalabs/Tower-Plus-2B-mlx](https://huggingface.co/ethicalabs/Tower-Plus-2B-mlx) was
+converted to MLX format from [Unbabel/Tower-Plus-2B](https://huggingface.co/Unbabel/Tower-Plus-2B)
+using mlx-lm version **0.28.3**.
+
+## Use with mlx
+
+```bash
+pip install mlx-lm
+```
+
+```python
+from mlx_lm import load, generate
+
+model, tokenizer = load("ethicalabs/Tower-Plus-2B-mlx")
+
+prompt = "hello"
+
+if tokenizer.chat_template is not None:
+    messages = [{"role": "user", "content": prompt}]
+    prompt = tokenizer.apply_chat_template(
+        messages, add_generation_prompt=True
+    )
+
+response = generate(model, tokenizer, prompt=prompt, verbose=True)
+```

chat_template.jinja

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+{{ bos_token }}{% for message in messages %}{% if message['role'] == 'assistant' %}{% set role = 'model' %}{% else %}{% set role = message['role'] %}{% endif %}<start_of_turn>{{ role }}
+{{ message['content'] | trim }}<end_of_turn>
+{% endfor %}{% if add_generation_prompt %}<start_of_turn>model
+{% endif %}

config.json

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+{
+    "architectures": [
+        "Gemma2ForCausalLM"
+    ],
+    "attention_bias": false,
+    "attention_dropout": 0.0,
+    "attn_logit_softcapping": 50.0,
+    "bos_token_id": 2,
+    "cache_implementation": "hybrid",
+    "eos_token_id": 107,
+    "final_logit_softcapping": 30.0,
+    "head_dim": 256,
+    "hidden_act": "gelu_pytorch_tanh",
+    "hidden_activation": "gelu_pytorch_tanh",
+    "hidden_size": 2304,
+    "initializer_range": 0.02,
+    "intermediate_size": 9216,
+    "max_position_embeddings": 8192,
+    "model_type": "gemma2",
+    "num_attention_heads": 8,
+    "num_hidden_layers": 26,
+    "num_key_value_heads": 4,
+    "pad_token_id": 0,
+    "query_pre_attn_scalar": 224,
+    "rms_norm_eps": 1e-06,
+    "rope_theta": 10000.0,
+    "sliding_window": 4096,
+    "torch_dtype": "bfloat16",
+    "transformers_version": "4.48.3",
+    "use_cache": false,
+    "vocab_size": 256000
+}

generation_config.json

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+{
+  "_from_model_config": true,
+  "bos_token_id": 2,
+  "cache_implementation": "hybrid",
+  "eos_token_id": 107,
+  "pad_token_id": 0,
+  "transformers_version": "4.48.3"
+}

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