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README.md

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+---
+language:
+- en
+- ja
+license: apache-2.0
+library_name: transformers
+tags:
+- mlx
+datasets:
+- databricks/databricks-dolly-15k
+- llm-jp/databricks-dolly-15k-ja
+- llm-jp/oasst1-21k-en
+- llm-jp/oasst1-21k-ja
+- llm-jp/oasst2-33k-en
+- llm-jp/oasst2-33k-ja
+programming_language:
+- C
+- C++
+- C#
+- Go
+- Java
+- JavaScript
+- Lua
+- PHP
+- Python
+- Ruby
+- Rust
+- Scala
+- TypeScript
+pipeline_tag: text-generation
+inference: false
+---
+
+# mlx-community/llm-jp-13b-instruct-full-ac_001-dolly-ichikara_004_001_single-oasst-oasst2-v2.0
+This model was converted to MLX format from [`llm-jp/llm-jp-13b-instruct-full-ac_001-dolly-ichikara_004_001_single-oasst-oasst2-v2.0`]() using mlx-lm version **0.12.0**.
+Refer to the [original model card](https://huggingface.co/llm-jp/llm-jp-13b-instruct-full-ac_001-dolly-ichikara_004_001_single-oasst-oasst2-v2.0) for more details on the model.
+## Use with mlx
+
+```bash
+pip install mlx-lm
+```
+
+```python
+from mlx_lm import load, generate
+
+model, tokenizer = load("mlx-community/llm-jp-13b-instruct-full-ac_001-dolly-ichikara_004_001_single-oasst-oasst2-v2.0")
+response = generate(model, tokenizer, prompt="hello", verbose=True)
+```

config.json

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+{
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+        "LlamaForCausalLM"
+    ],
+    "attention_bias": false,
+    "attention_dropout": 0.0,
+    "bos_token_id": 1,
+    "eos_token_id": 7,
+    "hidden_act": "silu",
+    "hidden_size": 5120,
+    "initializer_range": 0.02,
+    "intermediate_size": 13824,
+    "max_position_embeddings": 4096,
+    "max_sequence_length": 4096,
+    "model_type": "llama",
+    "num_attention_heads": 40,
+    "num_hidden_layers": 40,
+    "num_key_value_heads": 40,
+    "pad_token_id": 4,
+    "pretraining_tp": 1,
+    "rms_norm_eps": 1e-05,
+    "rope_scaling": null,
+    "rope_theta": 10000.0,
+    "tie_word_embeddings": false,
+    "torch_dtype": "bfloat16",
+    "transformers_version": "4.39.3",
+    "use_cache": false,
+    "vocab_size": 97024
+}

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special_tokens_map.json

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+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer_config.json

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+  ],
+  "bos_token": "<s|LLM-jp>",
+  "chat_template": "{% for message in messages %}{% if message['role'] == 'user' %}{{ '\\n\\n### 指示:\\n' + message['content'] }}{% elif message['role'] == 'system' %}{{ '以下は、タスクを説明する指示です。要求を適切に満たす応答を書きなさい。' }}{% elif message['role'] == 'assistant' %}{{ '\\n\\n### 応答:\\n' + message['content'] + eos_token }}{% endif %}{% if loop.last and add_generation_prompt %}{{ '\\n\\n### 応答:\\n' }}{% endif %}{% endfor %}",
+  "clean_up_tokenization_spaces": false,
+  "cls_token": "<CLS|LLM-jp>",
+  "eod_token": "<EOD|LLM-jp>",
+  "eos_token": "<EOD|LLM-jp>",
+  "extra_ids": 0,
+  "mask_token": "<mask|LLM-jp>",
+  "model_max_length": 1000000000000000019884624838656,
+  "pad_token": "<pad|LLM-jp>",
+  "sep_token": "<SEP|LLM-jp>",
+  "sp_model_kwargs": {},
+  "tokenizer_class": "PreTrainedTokenizerFast",
+  "unk_token": "<unk|LLM-jp>"
+}