Quant for 8.0

README.md

@@ -13,68 +13,167 @@ datasets:
 - microsoft/orca-math-word-problems-200k
 - Locutusque/function-calling-chatml
 - internlm/Agent-FLAN
-quantized_by: bartowski
-pipeline_tag: text-generation
 ---
 
-## Exllama v2 Quantizations of dolphin-2.9.3-mistral-7B-32k
+# Dolphin 2.9.3 Mistral 7b v0.3 32k 🐬
 
-Using <a href="https://github.com/turboderp/exllamav2/releases/tag/v0.1.6">turboderp's ExLlamaV2 v0.1.6</a> for quantization.
+Curated and trained by Eric Hartford and Cognitive Computations
 
-<b>The "main" branch only contains the measurement.json, download one of the other branches for the model (see below)</b>
+[![Discord](https://img.shields.io/discord/1156064224225808488?logo=Discord&logoColor=%23ffffff&label=Discord&link=https%3A%2F%2Fdiscord.gg%2FtCMkMDDHwm)](https://discord.gg/cognitivecomputations)
+Discord: https://discord.gg/cognitivecomputations
 
-Each branch contains an individual bits per weight, with the main one containing only the meaurement.json for further conversions.
+<img src="https://cdn-uploads.huggingface.co/production/uploads/63111b2d88942700629f5771/ldkN1J0WIDQwU4vutGYiD.png" width="600" />
 
-Original model: https://huggingface.co/cognitivecomputations/dolphin-2.9.3-mistral-7B-32k
+Our appreciation for the sponsors of Dolphin 2.9.3:
+- [Crusoe Cloud](https://crusoe.ai/) - provided excellent on-demand 8xH100 node
+- [OnDemand](https://on-demand.io/) - provided inference sponsorship
 
-## Prompt format
+This model is based on mistralai/Mistral-7B-v0.3, and is governed by the apache 2.0 license.
 
-```
-<|im_start|> system
-{system_prompt}<|im_end|> 
-<|im_start|> user
-{prompt}<|im_end|> 
-<|im_start|> assistant
+The base model has 32k context, and our finetuning took place with 8192 sequence length.
 
-```
+Dolphin 2.9.3 uses ChatML prompt template format.
 
-## Available sizes
+example:
 
+```
+<|im_start|>system
+You are Dolphin, a helpful AI assistant.<|im_end|>
+<|im_start|>user
+{prompt}<|im_end|>
+<|im_start|>assistant
 
-| Branch | Bits | lm_head bits | VRAM (4k) | VRAM (16k) | VRAM (32k) | Description |
-| ----- | ---- | ------- | ------ | ------ | ------ | ------------ |
-| [8_0](https://huggingface.co/bartowski/dolphin-2.9.3-mistral-7B-32k-exl2/tree/8_0) | 8.0 | 8.0 | 8.4 GB | 9.8 GB | 11.8 GB | Maximum quality that ExLlamaV2 can produce, near unquantized performance. |
-| [6_5](https://huggingface.co/bartowski/dolphin-2.9.3-mistral-7B-32k-exl2/tree/6_5) | 6.5 | 8.0 | 7.2 GB | 8.6 GB | 10.6 GB | Very similar to 8.0, good tradeoff of size vs performance, **recommended**. |
-| [5_0](https://huggingface.co/bartowski/dolphin-2.9.3-mistral-7B-32k-exl2/tree/5_0) | 5.0 | 6.0 | 6.0 GB | 7.4 GB |  9.4 GB | Slightly lower quality vs 6.5, but usable on 8GB cards. |
-| [4_25](https://huggingface.co/bartowski/dolphin-2.9.3-mistral-7B-32k-exl2/tree/4_25) | 4.25 | 6.0 | 5.3 GB | 6.7 GB | 8.7 GB | GPTQ equivalent bits per weight, slightly higher quality. |
-| [3_5](https://huggingface.co/bartowski/dolphin-2.9.3-mistral-7B-32k-exl2/tree/3_5) | 3.5 | 6.0 | 4.7 GB | 6.1 GB | 8.1 GB | Lower quality, only use if you have to. |
+```
 
-## Download instructions
+Dolphin-2.9.3 has a variety of instruction following, conversational, and coding skills. It also has initial agentic abilities and supports function calling.
 
-With git:
+Dolphin is uncensored. We have filtered the dataset to remove alignment and bias. This makes the model more compliant. You are advised to implement your own alignment layer before exposing the model as a service. It will be highly compliant with any requests, even unethical ones. Please read my blog post about uncensored models. https://erichartford.com/uncensored-models You are responsible for any content you create using this model. Enjoy responsibly.
 
-```shell
-git clone --single-branch --branch 6_5 https://huggingface.co/bartowski/dolphin-2.9.3-mistral-7B-32k-exl2 dolphin-2.9.3-mistral-7B-32k-exl2-6_5
-```
+Dolphin is licensed according to apache 2.0 license.  We grant permission for any use, including commercial. Dolphin was trained on data generated from GPT4, among other models.
 
-With huggingface hub (credit to TheBloke for instructions):
+## Evals
 
-```shell
-pip3 install huggingface-hub
-```
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/63111b2d88942700629f5771/5KUgfzJyY1IM4Yg6bg3Dq.png)
 
-To download a specific branch, use the `--revision` parameter. For example, to download the 6.5 bpw branch:
+## Training
 
-Linux:
+[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
+<details><summary>See axolotl config</summary>
 
-```shell
-huggingface-cli download bartowski/dolphin-2.9.3-mistral-7B-32k-exl2 --revision 6_5 --local-dir dolphin-2.9.3-mistral-7B-32k-exl2-6_5
-```
+axolotl version: `0.4.0`
+```yaml
+base_model: mistralai/Mistral-7B-v0.3
+model_type: AutoModelForCausalLM
+tokenizer_type: AutoTokenizer
 
-Windows (which apparently doesn't like _ in folders sometimes?):
+load_in_8bit: false
+# load_in_4bit: true
+strict: false
 
-```shell
-huggingface-cli download bartowski/dolphin-2.9.3-mistral-7B-32k-exl2 --revision 6_5 --local-dir dolphin-2.9.3-mistral-7B-32k-exl2-6.5
-```
+datasets:
+  - path: /workspace/datasets/dolphin-2.9.3/dolphin201-sharegpt2.jsonl
+    type: sharegpt
+    conversation: chatml
+  - path: /workspace/datasets/dolphin-2.9.3/SystemChat_filtered_sharegpt.jsonl
+    type: sharegpt
+    conversation: chatml
+  - path: /workspace/datasets/dolphin-2.9.3/SystemChat_multilingual_sharegpt.jsonl
+    type: sharegpt
+    conversation: chatml
+  - path: /workspace/datasets/dolphin-2.9.3/dolphin-coder-translate-sharegpt2.jsonl
+    type: sharegpt
+    conversation: chatml
+  - path: /workspace/datasets/dolphin-2.9.3/dolphin-coder-codegen-sharegpt2.jsonl
+    type: sharegpt
+    conversation: chatml
+  - path: /workspace/datasets/dolphin-2.9.3/m-a-p_Code-Feedback-sharegpt-unfiltered.jsonl
+    type: sharegpt
+    conversation: chatml
+  - path: /workspace/datasets/dolphin-2.9.3/m-a-p_CodeFeedback-Filtered-Instruction-sharegpt-unfiltered.jsonl
+    type: sharegpt
+    conversation: chatml
+  - path: /workspace/datasets/dolphin-2.9.3/not_samantha_norefusals.jsonl
+    type: sharegpt
+    conversation: chatml
+  - path: /workspace/datasets/dolphin-2.9.3/Orca-Math-resort-unfiltered.jsonl
+    type: sharegpt
+    conversation: chatml
+  - path: /workspace/datasets/dolphin-2.9.3/agent_instruct_react_unfiltered.jsonl
+    type: sharegpt  
+    conversation: chatml
+  - path: /workspace/datasets/dolphin-2.9.3/toolbench_instruct_j1s1_3k_unfiltered.jsonl
+    type: sharegpt  
+    conversation: chatml
+  - path: /workspace/datasets/dolphin-2.9.3/toolbench_negative_unfiltered.jsonl
+    type: sharegpt
+    conversation: chatml
+  - path: /workspace/datasets/dolphin-2.9.3/toolbench_react_10p_unfiltered.jsonl
+    type: sharegpt
+    conversation: chatml
+  - path: /workspace/datasets/dolphin-2.9.3/toolbench_tflan_cot_30p_unfiltered.jsonl
+    type: sharegpt
+    conversation: chatml
+  - path: /workspace/datasets/dolphin-2.9.3/openhermes200k_unfiltered.jsonl
+    type: sharegpt 
+    conversation: chatml
+
+chat_template: chatml
+# adapter: qlora
+# lora_r: 128
+# lora_alpha: 16
+# lora_modules_to_save: [embed_tokens, lm_head]
+# lora_dropout: 0.05
+# lora_target_linear: true
+
+
+dataset_prepared_path:  /workspace/axolotl/dolph-2.9.3-prepared
+val_set_size: 0.01
+output_dir: /workspace/axolotl/dolphin-2.9.3-mistral-7B
+
+sequence_len: 8192
+sample_packing: true
+pad_to_sequence_len: true
+
+wandb_project: dolphin-2.9.3-Mistral-7B
+wandb_watch:
+wandb_run_id:
+wandb_log_model:
+
+gradient_accumulation_steps: 16
+micro_batch_size: 1
+num_epochs: 3
+optimizer: adamw_8bit
+lr_scheduler: cosine
+learning_rate: 5e-6
+train_on_inputs: false
+group_by_length: false
+bf16: auto
+fp16:
+tf32:
+
+gradient_checkpointing: true
+gradient_checkpointing_kwargs:
+  use_reentrant: false
+early_stopping_patience:
+resume_from_checkpoint:
+logging_steps: 1
+xformers_attention:
+flash_attention: true
+
+warmup_steps: 100
+# evals_per_epoch: 4
+eval_table_size:
+saves_per_epoch: 1
+save_total_limit: 2
+save_steps:
+debug:
+deepspeed: /workspace/axolotl/deepspeed_configs/zero3_bf16.json
+weight_decay: 0.1
+fsdp:
+fsdp_config:
+special_tokens:
+  eos_token: "<|im_end|>"
+tokens:
+  - "<|im_start|>"
 
-Want to support my work? Visit my ko-fi page here: https://ko-fi.com/bartowski
+```

added_tokens.json

@@ -0,0 +1,4 @@
+{
+  "<|im_end|>": 32768,
+  "<|im_start|>": 32769
+}

config.json

@@ -0,0 +1,37 @@
+{
+    "_name_or_path": "mistralai/Mistral-7B-v0.3",
+    "architectures": [
+        "MistralForCausalLM"
+    ],
+    "attention_dropout": 0.0,
+    "bos_token_id": 1,
+    "eos_token_id": 32768,
+    "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": 1000000.0,
+    "sliding_window": null,
+    "tie_word_embeddings": false,
+    "torch_dtype": "bfloat16",
+    "transformers_version": "4.41.1",
+    "use_cache": false,
+    "vocab_size": 32770,
+    "quantization_config": {
+        "quant_method": "exl2",
+        "version": "0.1.6",
+        "bits": 8.0,
+        "head_bits": 8,
+        "calibration": {
+            "rows": 115,
+            "length": 2048,
+            "dataset": "(default)"
+        }
+    }
+}

generation_config.json

@@ -0,0 +1,7 @@
+{
+  "_from_model_config": true,
+  "bos_token_id": 1,
+  "do_sample": true,
+  "eos_token_id": 2,
+  "transformers_version": "4.41.1"
+}

model.safetensors.index.json

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