Quant for 3.5

README.md

@@ -8,69 +8,41 @@ datasets:
 language:
 - zh
 - en
-quantized_by: bartowski
-pipeline_tag: text-generation
 ---
+# **BLOSSOM-v5-9b**
 
-## Exllama v2 Quantizations of blossom-v5-9b
+[💻Github](https://github.com/Azure99/BlossomLM) • [🚀Blossom Chat Demo](https://blossom-chat.com/)
 
-Using <a href="https://github.com/turboderp/exllamav2/releases/tag/v0.0.15">turboderp's ExLlamaV2 v0.0.15</a> for quantization.
+### What's new?
 
-## The "main" branch only contains the measurement.json, download one of the other branches for the model (see below)
+The Blossom V5 series models is fully trained using high-quality data distilled from gpt-4-0125-preview, resulting in significant improvements.
 
-Each branch contains an individual bits per weight, with the main one containing only the meaurement.json for further conversions.
+### Introduction
 
-Conversion was done using the default calibration dataset.
+Blossom is a conversational large language model, fine-tuned on the Blossom Orca/Wizard/Chat/Math mixed dataset based on the Yi-9B pre-trained model. Blossom possesses robust general capabilities and context comprehension. Additionally, the high-quality Chinese and English datasets used for training have been made open source.
 
-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.
+Training was conducted in two stages. The first stage used 40K Wizard, 40K Orca, 10K Math single-turn instruction datasets, training for 1 epoch; the second stage used 10K Blossom chat multi-turn dialogue dataset, and 10% randomly sampled data from the first stage, training for 3 epochs.
 
-Original model: https://huggingface.co/Azure99/blossom-v5-9b
+### Inference
 
+Inference is performed in the form of dialogue continuation.
 
-<a href="https://huggingface.co/bartowski/blossom-v5-9b-exl2/tree/8_0">8.0 bits per weight</a>
+Single-turn dialogue
 
-<a href="https://huggingface.co/bartowski/blossom-v5-9b-exl2/tree/6_5">6.5 bits per weight</a>
-
-<a href="https://huggingface.co/bartowski/blossom-v5-9b-exl2/tree/5_0">5.0 bits per weight</a>
-
-<a href="https://huggingface.co/bartowski/blossom-v5-9b-exl2/tree/4_25">4.25 bits per weight</a>
-
-<a href="https://huggingface.co/bartowski/blossom-v5-9b-exl2/tree/3_5">3.5 bits per weight</a>
-
-
-## Download instructions
-
-With git:
-
-```shell
-git clone --single-branch --branch 6_5 https://huggingface.co/bartowski/blossom-v5-9b-exl2
 ```
-
-With huggingface hub (credit to TheBloke for instructions):
-
-```shell
-pip3 install huggingface-hub
+A chat between a human and an artificial intelligence bot. The bot gives helpful, detailed, and polite answers to the human's questions.
+|Human|: hello
+|Bot|: 
 ```
 
-To download the `main` (only useful if you only care about measurement.json) branch to a folder called `blossom-v5-9b-exl2`:
+Multi-turn dialogue
 
-```shell
-mkdir blossom-v5-9b-exl2
-huggingface-cli download bartowski/blossom-v5-9b-exl2 --local-dir blossom-v5-9b-exl2 --local-dir-use-symlinks False
 ```
-
-To download from a different branch, add the `--revision` parameter:
-
-Linux:
-
-```shell
-mkdir blossom-v5-9b-exl2-6_5
-huggingface-cli download bartowski/blossom-v5-9b-exl2 --revision 6_5 --local-dir blossom-v5-9b-exl2-6_5 --local-dir-use-symlinks False
+A chat between a human and an artificial intelligence bot. The bot gives helpful, detailed, and polite answers to the human's questions.
+|Human|: hello
+|Bot|: Hello! How can I assist you today?<|endoftext|>
+|Human|: Generate a random number using python
+|Bot|: 
 ```
 
-Windows (which apparently doesn't like _ in folders sometimes?):
-
-```shell
-mkdir blossom-v5-9b-exl2-6.5
-huggingface-cli download bartowski/blossom-v5-9b-exl2 --revision 6_5 --local-dir blossom-v5-9b-exl2-6.5 --local-dir-use-symlinks False
-```
+Note: At the end of the Bot's output in the historical conversation, append a `<|endoftext|>`.

config.json

@@ -0,0 +1,29 @@
+{
+  "_name_or_path": "/mnt/output/yi-9b_5-stage1",
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "hidden_act": "silu",
+  "hidden_size": 4096,
+  "initializer_range": 0.02,
+  "intermediate_size": 11008,
+  "max_position_embeddings": 4096,
+  "model_type": "llama",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 48,
+  "num_key_value_heads": 4,
+  "pad_token_id": 0,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-06,
+  "rope_scaling": null,
+  "rope_theta": 10000,
+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.38.2",
+  "use_cache": true,
+  "vocab_size": 64000
+}

generation_config.json

@@ -0,0 +1,7 @@
+{
+  "_from_model_config": true,
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "pad_token_id": 0,
+  "transformers_version": "4.38.2"
+}

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