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README.md

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+---
+license: other
+---
+
+---
+
+This is a [ggml](https://github.com/ggerganov/ggml/) quantized version of [Replit-v2-CodeInstruct-3B](https://huggingface.co/teknium/Replit-v2-CodeInstruct-3B). Quantized to 4bit -> q4_1.
+To run inference you can use ggml directly or [ctransformers](https://github.com/marella/ctransformers).
+
+- Memory usage of model: **2GB~**
+- Repo to run the model using ctransformers: https://github.com/abacaj/replit-3B-inference

config.json

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+{
+  "architectures": [
+    "MPTForCausalLM"
+  ],
+  "attn_config": {
+    "alibi": true,
+    "alibi_bias_max": 8,
+    "attn_impl": "torch",
+    "attn_pdrop": 0,
+    "attn_type": "multihead_attention",
+    "attn_uses_sequence_id": false,
+    "clip_qkv": null,
+    "prefix_lm": false,
+    "qk_ln": false,
+    "softmax_scale": null
+  },
+  "auto_map": {
+    "AutoConfig": "configuration_mpt.MPTConfig",
+    "AutoModelForCausalLM": "modeling_mpt.MPTForCausalLM"
+  },
+  "d_model": 2560,
+  "emb_pdrop": 0,
+  "embedding_fraction": 1.0,
+  "expansion_ratio": 4,
+  "init_config": {
+    "emb_init_std": null,
+    "emb_init_uniform_lim": null,
+    "fan_mode": "fan_in",
+    "init_div_is_residual": true,
+    "init_gain": 0,
+    "init_nonlinearity": "relu",
+    "init_std": 0.02,
+    "name": "kaiming_normal_",
+    "verbose": 0
+  },
+  "init_device": "cpu",
+  "learned_pos_emb": true,
+  "logit_scale": null,
+  "max_seq_len": 2048,
+  "model_type": "mpt",
+  "n_heads": 32,
+  "n_layers": 32,
+  "no_bias": true,
+  "norm_type": "low_precision_layernorm",
+  "resid_pdrop": 0,
+  "tokenizer_name": "teknium/Replit-v2-CodeInstruct-3B",
+  "torch_dtype": "float16",
+  "transformers_version": "4.29.2",
+  "use_cache": false,
+  "verbose": 0,
+  "vocab_size": 32768
+}

gitattributes.txt

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q4.bin

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