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README.md

@@ -2,65 +2,10 @@
 license: cc-by-4.0
 language:
 - en
-pipeline_tag: text-generation
 tags:
-- mistral
 - merge
 ---
-# Sakura-SOLAR-Instruct
-
-- Model creator: [Sanji Watsuki](https://huggingface.co/SanjiWatsuki)
-- Original model: [Sonya-7B](https://huggingface.co/SanjiWatsuki/Sonya-7B)
-- Is a merge of:
-  - [xDAN-AI/xDAN-L1-Chat-RL-v1](https://huggingface.co/xDAN-AI/xDAN-L1-Chat-RL-v1)
-  - [jan-hq/stealth-v1.2](https://huggingface.co/jan-hq/stealth-v1.2)
-  - [chargoddard/piano-medley-7b](https://huggingface.co/chargoddard/piano-medley-7b)
-  - [NeverSleep/Noromaid-7b-v0.2](https://huggingface.co/NeverSleep/Noromaid-7b-v0.2)
-  - [athirdpath/NSFW_DPO_vmgb-7b](https://huggingface.co/athirdpath/NSFW_DPO_vmgb-7b)
-
-## Quantizations
-I also provide zipped quantization because a lot of people find gguf single download convenient. Zipped quantization is relatively smaller in size to download. After extracted, you can use the model folder as usual.
-
-<details>
-  <summary>Parameter Explanation</summary>
-  
-- **BPW**: Bits per weight of the quantized model.
-- **Folder Size**: Size of the model folder in GB when stored on disk or after extracted from zip file.
-- **Zipped Folder Size**: Size of the zipped file after downloaded.
-- **VRAM Usage**: VRAM usage of the model measured using ExLlamav2_HF and 4096 max_seq_len with [Oobabooga's Text Generation WebUI](https://github.com/oobabooga/text-generation-webui/tree/main).
-- **Loss**: Accuracy loss of the quantized model compared to the original model.
-- **Description**: Recommended GPU and/or settings for the model.
-
-</details>
-
-On the table, I included VRAM usages of both 4096 max_seq_len and 8192 max_seq_len as a comparison. Sonya-7B default max_seq_len is 8192.
-
-| Branch | BPW | Folder Size | Zipped File Size | VRAM Usage (4096/8192) | Loss | Description |
-| ------ | --- | ----------- | ---------------- | ---------------------- | ---- | ----------- |
-[2.0bpw](https://huggingface.co/hgloow/Sonya-7B-EXL2/tree/2.0bpw)/[2.0bpw-zip](https://huggingface.co/hgloow/Sonya-7B-EXL2/tree/2.0bpw-zip)|2.0BPW|2.15GB|1.80GB|3.1GB/3.5GB|~14%|For >=4GB VRAM cards with idle VRAM atleast or below 500MB (headroom for other things)
-[2.4bpw](https://huggingface.co/hgloow/Sonya-7B-EXL2/tree/2.4bpw)/[2.4bpw-zip](https://huggingface.co/hgloow/Sonya-7B-EXL2/tree/2.4bpw-zip)|2.4BPW|2.29GB|1.98GB|3.3GB/3.7GB|~13%|For >=4GB VRAM cards (4096 max_seq_len)
-[3.5bpw](https://huggingface.co/hgloow/Sonya-7B-EXL2/tree/3.5bpw)/[3.5bpw-zip](https://huggingface.co/hgloow/Sonya-7B-EXL2/tree/3.5bpw-zip)|3.5BPW|3.19GB|2.91GB|4.2GB/4.6GB|~7%|For >=5GB VRAM cards (4096 max_seq_len)
-[4.5bpw (main)](https://huggingface.co/hgloow/Sonya-7B-EXL2/tree/main)/[4.5bpw-zip](https://huggingface.co/hgloow/Sonya-7B-EXL2/tree/4.5bpw-zip)|4.5BPW|4.0GB|3.77GB|5.0GB/5.3GB|~4%|For >=6GB VRAM cards with idle VRAM atleast or below 500MB (headroom for other things)
-[4.75bpw](https://huggingface.co/hgloow/Sonya-7B-EXL2/tree/4.75bpw)/[4.75bpw-zip](https://huggingface.co/hgloow/Sonya-7B-EXL2/tree/4.75bpw-zip)|4.75BPW|4.2GB|4.0GB|5.2GB/5.6GB|~3%|For >=6GB VRAM cards (4096 max_seq_len)
-[7.0bpw](https://huggingface.co/hgloow/Sonya-7B-EXL2/tree/7.0bpw)/[7.0bpw-zip](https://huggingface.co/hgloow/Sonya-7B-EXL2/tree/7.0bpw-zip)|7.0BPW|6.03GB|5.74GB|7GB/7.3GB|~1%|For >=8GB VRAM cards with idle VRAM atleast or below 500MB (headroom for other things)
-
-Unfortunately I couldn't make higher quants than 7.0bpw. No error on the console, just "Killed" after creating output directory for the model.
-
-## Calibration Dataset
-- Exllamav2 default dataset
-
-## Prompt template: Alpaca
-```
-Below is an instruction that describes a task. Write a response that appropriately completes the request.
-
-### Instruction:
-{prompt}
-
-### Response:
-
-```
 
-# Original Info
 <div style="display: flex; justify-content: center; align-items: center">
   <img src="https://huggingface.co/SanjiWatsuki/Sonya-7B/resolve/main/assets/Sonya.jpg">
 </div
@@ -181,4 +126,4 @@ I found that this model **performed worse** with the xDAN prompt format so, desp
 | vicuna-33b-v1.3    | 2    | 6.787500  |  33b
 | Llama-2-70b-chat   | 2    | 6.725000  |  70b
 
-If you'd like to replicate the MT-Bench run, please ensure that the Alpaca prompt template is applied to the model. I did this by putting "alpaca" in the model path to trigger the `AlpacaAdapter`. 
+If you'd like to replicate the MT-Bench run, please ensure that the Alpaca prompt template is applied to the model. I did this by putting "alpaca" in the model path to trigger the `AlpacaAdapter`. 

config.json

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+{
+  "_name_or_path": "mistralai/Mistral-7B-v0.1",
+  "architectures": [
+    "MistralForCausalLM"
+  ],
+  "attention_dropout": 0.0,
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "hidden_act": "silu",
+  "hidden_size": 4096,
+  "initializer_range": 0.02,
+  "intermediate_size": 14336,
+  "max_position_embeddings": 8192,
+  "model_type": "mistral",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 32,
+  "num_key_value_heads": 8,
+  "rms_norm_eps": 1e-05,
+  "rope_theta": 10000.0,
+  "sliding_window": 4096,
+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.37.0.dev0",
+  "use_cache": true,
+  "vocab_size": 32000
+}

huggingface-metadata.txt

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+url: https://huggingface.co/SanjiWatsuki/Sonya-7B
+branch: main
+download date: 2024-01-01 09:19:02
+sha256sum:
+    84ca39c268868ef302966ed5dab6f72815718b0041c90a2190acb1f2d40c634c model-00001-of-00002.safetensors
+    425ec418e9b61fff4c2b5906afb523fdd733c3b0225e13e1e98a53097b523290 model-00002-of-00002.safetensors
+    dadfd56d766715c61d2ef780a525ab43b8e6da4de6865bda3d95fdef5e134055 tokenizer.model

model.safetensors.index.json

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