Quant for 3.5

.gitattributes

@@ -1,35 +1,4 @@
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README.md

@@ -25,59 +25,102 @@ model-index:
       type: pass@1
       value: 34.146
       verified: false
-quantized_by: bartowski
 ---
 
-## Exllama v2 Quantizations of speechless-mistral-dolphin-orca-platypus-samantha-7b
+<p><h1> speechless-mistral-dolphin-orca-platypus-samantha-7b </h1></p>
 
-Using <a href="https://github.com/turboderp/exllamav2/releases/tag/v0.0.11">turboderp's ExLlamaV2 v0.0.11</a> for quantization.
+* [AWQ model(s) for GPU inference.](https://huggingface.co/TheBloke/speechless-mistral-dolphin-orca-platypus-samantha-7B-AWQ)
+* [GPTQ models for GPU inference, with multiple quantisation parameter options.](https://huggingface.co/TheBloke/speechless-mistral-dolphin-orca-platypus-samantha-7B-GPTQ)
+* [2, 3, 4, 5, 6 and 8-bit GGUF models for CPU+GPU inference](https://huggingface.co/TheBloke/speechless-mistral-dolphin-orca-platypus-samantha-7B-GGUF)
 
-# The "main" branch only contains the measurement.json, download one of the other branches for the model (see below)
+This model is a merge of ehartford/dolphin-2.1-mistral-7b, Open-Orca/Mistral-7B-OpenOrca, bhenrym14/mistral-7b-platypus-fp16 and ehartford/samantha-1.2-mistral-7b.
 
-Each branch contains an individual bits per weight, with the main one containing only the meaurement.json for further conversions.
+I'm very sorry for giving such a long and peculiar name. Originally, it was just my lazy behavior during the process of making models to easily distinguish various model and dataset combinations. I didn't expect the [previous model](https://huggingface.co/uukuguy/speechless-llama2-hermes-orca-platypus-wizardlm-13b) ([Thebloke GPTQ Version](https://huggingface.co/TheBloke/Speechless-Llama2-Hermes-Orca-Platypus-WizardLM-13B-GPTQ)) to be so popular. This time, based on some guys's request, I am releasing a model based on Mistral, and I have also inherited the style of the super long name along with it. Welcome to try the model, please refrain from harsh criticism if you don't like it.
 
-Conversion was done using the default calibration dataset.
+Code: https://github.com/uukuguy/speechless
 
-Default arguments used except when the bits per weight is above 6.0, at that point the lm_head layer is quantized at 8 bits per weight instead of the default 6.
+## HumanEval
 
-Original model: https://huggingface.co/uukuguy/speechless-mistral-dolphin-orca-platypus-samantha-7b
+| Metric | Value |
+| --- | --- |
+| humaneval-python |  34.146|
 
+[Big Code Models Leaderboard](https://huggingface.co/spaces/bigcode/bigcode-models-leaderboard)
 
+CodeLlama-34B-Python: 53.29
 
-<a href="https://huggingface.co/bartowski/speechless-mistral-dolphin-orca-platypus-samantha-7b-exl2/tree/8_0">8.0 bits per weight</a>
+CodeLlama-34B-Instruct: 50.79
 
-<a href="https://huggingface.co/bartowski/speechless-mistral-dolphin-orca-platypus-samantha-7b-exl2/tree/6_5">6.5 bits per weight</a>
+CodeLlama-13B-Instruct: 50.6
 
-<a href="https://huggingface.co/bartowski/speechless-mistral-dolphin-orca-platypus-samantha-7b-exl2/tree/5_0">5.0 bits per weight</a>
+CodeLlama-34B: 45.11
 
-<a href="https://huggingface.co/bartowski/speechless-mistral-dolphin-orca-platypus-samantha-7b-exl2/tree/4_0">4.0 bits per weight</a>
+CodeLlama-13B-Python: 42.89
 
-<a href="https://huggingface.co/bartowski/speechless-mistral-dolphin-orca-platypus-samantha-7b-exl2/tree/3_5">3.5 bits per weight</a>
+CodeLlama-13B: 35.07 
 
-## Download instructions
+Mistral-7B-v0.1: 30.488
 
-With git:
+## LM-Evaluation-Harness
 
-```shell
-git clone --single-branch --branch 4_0 https://huggingface.co/bartowski/speechless-mistral-dolphin-orca-platypus-samantha-7b-exl2
-```
+[Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
 
-With huggingface hub (credit to TheBloke for instructions):
+| Metric | Value |
+| --- | --- |
+| ARC | 64.33 |
+| HellaSwag | 84.4|
+| MMLU | 63.72 |
+| TruthfulQA | 52.52|
+| Winogrande | 78.37 |
+| GSM8K | 21.38 |
+| DROP | 8.66 |
+| Average | 53.34 |
 
-```shell
-pip3 install huggingface-hub
-```
+# Model Card for Mistral-7B-v0.1
 
-To download the `main` (only useful if you only care about measurement.json) branch to a folder called `speechless-mistral-dolphin-orca-platypus-samantha-7b-exl2`:
+The Mistral-7B-v0.1 Large Language Model (LLM) is a pretrained generative text model with 7 billion parameters. 
+Mistral-7B-v0.1 outperforms Llama 2 13B on all benchmarks we tested.
 
-```shell
-mkdir speechless-mistral-dolphin-orca-platypus-samantha-7b-exl2
-huggingface-cli download bartowski/speechless-mistral-dolphin-orca-platypus-samantha-7b-exl2 --local-dir speechless-mistral-dolphin-orca-platypus-samantha-7b-exl2 --local-dir-use-symlinks False
-```
+For full details of this model please read our [paper](https://arxiv.org/abs/2310.06825) and [release blog post](https://mistral.ai/news/announcing-mistral-7b/).
 
-To download from a different branch, add the `--revision` parameter:
+## Model Architecture
 
-```shell
-mkdir speechless-mistral-dolphin-orca-platypus-samantha-7b-exl2
-huggingface-cli download bartowski/speechless-mistral-dolphin-orca-platypus-samantha-7b-exl2 --revision 4_0 --local-dir speechless-mistral-dolphin-orca-platypus-samantha-7b-exl2 --local-dir-use-symlinks False
-```
+Mistral-7B-v0.1 is a transformer model, with the following architecture choices:
+- Grouped-Query Attention
+- Sliding-Window Attention
+- Byte-fallback BPE tokenizer
+
+## Troubleshooting
+
+- If you see the following error:
+``
+KeyError: 'mistral'
+``
+- Or:
+``
+NotImplementedError: Cannot copy out of meta tensor; no data!
+``
+
+Ensure you are utilizing a stable version of Transformers, 4.34.0 or newer.
+
+## Notice
+
+Mistral 7B is a pretrained base model and therefore does not have any moderation mechanisms.
+
+## The Mistral AI Team
+ 
+Albert Jiang, Alexandre Sablayrolles, Arthur Mensch, Chris Bamford, Devendra Singh Chaplot, Diego de las Casas, Florian Bressand, Gianna Lengyel, Guillaume Lample, Lélio Renard Lavaud, Lucile Saulnier, Marie-Anne Lachaux, Pierre Stock, Teven Le Scao, Thibaut Lavril, Thomas Wang, Timothée Lacroix, William El Sayed.`
+
+# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
+Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_uukuguy__speechless-mistral-dolphin-orca-platypus-samantha-7b)
+
+| Metric                | Value                     |
+|-----------------------|---------------------------|
+| Avg.                  | 53.34   |
+| ARC (25-shot)         | 64.33          |
+| HellaSwag (10-shot)   | 84.4    |
+| MMLU (5-shot)         | 63.72         |
+| TruthfulQA (0-shot)   | 52.52   |
+| Winogrande (5-shot)   | 78.37   |
+| GSM8K (5-shot)        | 21.38        |
+| DROP (3-shot)         | 8.66         |

added_tokens.json

@@ -0,0 +1,5 @@
+{
+  "</s>": 2,
+  "<s>": 1,
+  "<unk>": 0
+}

config.json

@@ -0,0 +1,25 @@
+{
+  "_name_or_path": "/opt/local/llm_models/huggingface.co/mistralai/Mistral-7B-v0.1",
+  "architectures": [
+    "MistralForCausalLM"
+  ],
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "hidden_act": "silu",
+  "hidden_size": 4096,
+  "initializer_range": 0.02,
+  "intermediate_size": 14336,
+  "max_position_embeddings": 32768,
+  "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": "4.34.0",
+  "use_cache": true,
+  "vocab_size": 32000
+}

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