Upload folder using huggingface_hub (#1)

- 6bb7f11fabf1ee0464ceef9df391e776eedb7640a50fe96c08b91ce5f75b6f90 (1712cf4fad13fc500929b621e32cff6427c30eeb)

README.md

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+---
+language:
+- ja
+- en
+license: other
+license_link: LICENSE
+tags:
+- mlx
+base_model: sbintuitions/sarashina2.1-1b
+---
+
+# mlx-community/sarashina2.1-1b-8bit
+
+The Model [mlx-community/sarashina2.1-1b-8bit](https://huggingface.co/mlx-community/sarashina2.1-1b-8bit) was
+converted to MLX format from [sbintuitions/sarashina2.1-1b](https://huggingface.co/sbintuitions/sarashina2.1-1b)
+using mlx-lm version **0.20.2**.
+
+## Use with mlx
+
+```bash
+pip install mlx-lm
+```
+
+```python
+from mlx_lm import load, generate
+
+model, tokenizer = load("mlx-community/sarashina2.1-1b-8bit")
+
+prompt="hello"
+
+if hasattr(tokenizer, "apply_chat_template") and tokenizer.chat_template is not None:
+    messages = [{"role": "user", "content": prompt}]
+    prompt = tokenizer.apply_chat_template(
+        messages, tokenize=False, add_generation_prompt=True
+    )
+
+response = generate(model, tokenizer, prompt=prompt, 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": 2,
+    "hidden_act": "silu",
+    "hidden_size": 1792,
+    "initializer_range": 0.02,
+    "intermediate_size": 6272,
+    "max_position_embeddings": 8192,
+    "mlp_bias": false,
+    "model_type": "llama",
+    "num_attention_heads": 16,
+    "num_hidden_layers": 24,
+    "num_key_value_heads": 8,
+    "pretraining_tp": 1,
+    "quantization": {
+        "group_size": 64,
+        "bits": 8
+    },
+    "quantization_config": {
+        "group_size": 64,
+        "bits": 8
+    },
+    "rms_norm_eps": 1e-05,
+    "rope_scaling": null,
+    "rope_theta": 500000,
+    "tie_word_embeddings": false,
+    "torch_dtype": "bfloat16",
+    "transformers_version": "4.40.1",
+    "use_cache": true,
+    "vocab_size": 102400
+}

model.safetensors

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