Quant for 5.0

README.md

@@ -15,63 +15,192 @@ datasets:
 - derek-thomas/ScienceQA
 - wenhu/TheoremQA
 - TIGER-Lab/ScienceEval
-quantized_by: bartowski
-pipeline_tag: text-generation
 ---
+![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/6468ce47e134d050a58aa89c/uvfa4GVWrnd8SS6yBxRJZ.jpeg)
 
-## Exllama v2 Quantizations of Einstein-7B
+# 🔬 Einstein-7B
 
-Using <a href="https://github.com/turboderp/exllamav2/releases/tag/v0.0.12">turboderp's ExLlamaV2 v0.0.12</a> for quantization.
+This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on datasets related to science.
 
-# The "main" branch only contains the measurement.json, download one of the other branches for the model (see below)
+This model is fine-tuned using [QLoRa](https://arxiv.org/abs/2305.14314) and [axolotl](https://github.com/OpenAccess-AI-Collective/axolotl).
 
-Each branch contains an individual bits per weight, with the main one containing only the meaurement.json for further conversions.
+This model's training was sponsored by [sablo.ai](https://sablo.ai).
 
-Original model: https://huggingface.co/Weyaxi/Einstein-7B
+<details><summary>See axolotl config</summary>
 
-| Branch | Bits | lm_head bits | Size | Description |
-| ----- | ---- | ------- | ------ | ------------ |
-| [8_0](https://huggingface.co/Bartowski/Einstein-7B-exl2/tree/8_0) | 8.0 | 8.0 | 9.8 GB | Maximum quality that ExLlamaV2 can produce, near unquantized performance. |
-| [6_5](https://huggingface.co/Bartowski/Einstein-7B-exl2/tree/6_5) | 6.5 | 8.0 | 8.6 GB | Very similar to 8.0, good tradeoff of size vs performance, **recommended**. |
-| [5_0](https://huggingface.co/Bartowski/Einstein-7B-exl2/tree/5_0) | 5.0 | 6.0 | 7.4 GB | Slightly lower quality vs 6.5, but usable on 8GB cards. |
-| [4_25](https://huggingface.co/Bartowski/Einstein-7B-exl2/tree/4_25) | 4.25 | 6.0 | 6.7 GB | GPTQ equivalent bits per weight, slightly higher quality. |
-| [3_5](https://huggingface.co/Bartowski/Einstein-7B-exl2/tree/3_5) | 3.5 | 6.0 | 6.1 GB | Lower quality, only use if you have to. |
-
-All VRAM requirements estimated from 16k context. For 32k context add ~2 GB.
+axolotl version: `0.3.0`
+```yaml
+base_model: mistralai/Mistral-7B-v0.1
+model_type: MistralForCausalLM
+tokenizer_type: LlamaTokenizer
+is_mistral_derived_model: true
 
-## Download instructions
+load_in_8bit: false
+load_in_4bit: true
+strict: false
 
-With git:
+datasets:
+  - path: sci-datasets/arc_challange_train_alpaca.json
+    ds_type: json
+    type: alpaca
+
+  - path: sci-datasets/camelai_biology_alpaca.json
+    ds_type: json
+    type: alpaca
+
+  - path: sci-datasets/camelai_chemistry_alpaca.json
+    ds_type: json
+    type: alpaca
+
+  - path: sci-datasets/camelai_physics_alpaca.json
+    ds_type: json
+    type: alpaca
+
+  - path: sci-datasets/openbookqa_alpaca.json
+    ds_type: json
+    type: alpaca
+
+  - path: sci-datasets/reclor_science_alpaca.json
+    ds_type: json
+    type: alpaca
+    
+  - path: sci-datasets/scibench_alpaca.json
+    ds_type: json
+    type: alpaca
+
+  - path: sci-datasets/scienceqa_alpaca.json
+    ds_type: json
+    type: alpaca
+
+  - path: sci-datasets/theoremqa_alpaca.json
+    ds_type: json
+    type: alpaca
+
+  - path: sci-datasets/tiger_scienceeval_alpaca.json
+    ds_type: json
+    type: alpaca
+
+dataset_prepared_path: last_run_prepared
+val_set_size: 0
+output_dir: ./science-mistral
+
+adapter: qlora
+lora_model_dir:
+
+sequence_len: 8192
+sample_packing: true
+pad_to_sequence_len: true
+
+lora_r: 128
+lora_alpha: 64
+lora_dropout: 0.05
+lora_target_linear: true
+lora_fan_in_fan_out:
+lora_target_modules:
+  - gate_proj
+  - down_proj
+  - up_proj
+  - q_proj
+  - v_proj
+  - k_proj
+  - o_proj
+
+wandb_project: huggingface
+wandb_entity:
+wandb_watch:
+wandb_name:
+wandb_log_model:
+hub_model_id: Weyaxi/science-mistral
+
+# change #
+gradient_accumulation_steps: 12
+micro_batch_size: 6
+num_epochs: 2
+optimizer: adamw_bnb_8bit
+lr_scheduler: cosine
+learning_rate: 0.0002
+# change #
+
+train_on_inputs: false
+group_by_length: false
+bf16: true
+fp16: false
+tf32: false
+
+gradient_checkpointing: true
+early_stopping_patience:
+resume_from_checkpoint:
+local_rank:
+logging_steps: 1
+xformers_attention:
+flash_attention: true
+
+warmup_steps: 10
+
+
+saves_per_epoch: 3
+debug:
+deepspeed:
+weight_decay: 0.1
+fsdp:
+fsdp_config:
+special_tokens:
+  bos_token: "<s>"
+  eos_token: "</s>"
+  unk_token: "<unk>"
 
-```shell
-git clone --single-branch --branch 6_5 https://huggingface.co/bartowski/Einstein-7B-exl2 Einstein-7B-exl2-6_5
 ```
 
-With huggingface hub (credit to TheBloke for instructions):
+</details><br>
 
-```shell
-pip3 install huggingface-hub
-```
+# 📊 Datasets
+
+Following datasets were used in this model:
+
+- [ARC](https://huggingface.co/datasets/allenai/ai2_arc) (Note: Only **train** part)
+
+- [camel-ai/physics](https://huggingface.co/datasets/camel-ai/physics)
+
+- [camel-ai/chemistry](https://huggingface.co/datasets/camel-ai/chemistry)
+
+- [camel-ai/biology](https://huggingface.co/datasets/camel-ai/biology)
+
+- [openbookqa](https://huggingface.co/datasets/openbookqa)
 
-To download the `main` (only useful if you only care about measurement.json) branch to a folder called `Einstein-7B-exl2`:
+- [reclor](https://huggingface.co/datasets/metaeval/reclor)
+
+- [scibench](https://github.com/mandyyyyii/scibench)
+
+- [ScienceQA](https://huggingface.co/datasets/derek-thomas/ScienceQA)
+
+- [TheoremQA](https://huggingface.co/datasets/wenhu/TheoremQA)
+
+- [ScienceEval](https://huggingface.co/datasets/TIGER-Lab/ScienceEval)
+
+# 💬 Prompt Template
+
+You can use this prompt template while using the model:
+
+### Alpaca
 
-```shell
-mkdir Einstein-7B-exl2
-huggingface-cli download bartowski/Einstein-7B-exl2 --local-dir Einstein-7B-exl2 --local-dir-use-symlinks False
 ```
+Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.
 
-To download from a different branch, add the `--revision` parameter:
+### Instruction:
+{instruction}
 
-Linux:
+### Input:
+{input}
 
-```shell
-mkdir Einstein-7B-exl2-6_5
-huggingface-cli download bartowski/Einstein-7B-exl2 --revision 6_5 --local-dir Einstein-7B-exl2-6_5 --local-dir-use-symlinks False
+### Response:
 ```
 
-Windows (which apparently doesn't like _ in folders sometimes?):
+# 🤝 Acknowledgments
+
+Thanks to Platypus for providing scripts to convert some of the datasets to Alpaca format: [Platypus/data_pipeline](https://github.com/arielnlee/Platypus/tree/main/data_pipeline)
+
+Thanks to all the dataset authors mentioned in the datasets section.
+
+Thanks to [axolotl](https://github.com/OpenAccess-AI-Collective/axolotl) for making the repository I used to make this model.
 
-```shell
-mkdir Einstein-7B-exl2-6.5
-huggingface-cli download bartowski/Einstein-7B-exl2 --revision 6_5 --local-dir Einstein-7B-exl2-6.5 --local-dir-use-symlinks False
-```
+[<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)

config.json

@@ -0,0 +1,26 @@
+{
+  "_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": 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": "4.37.0",
+  "use_cache": false,
+  "vocab_size": 32000
+}

generation_config.json

@@ -0,0 +1,6 @@
+{
+  "_from_model_config": true,
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "transformers_version": "4.37.0"
+}

original_repo_url.txt

@@ -0,0 +1 @@
+https://huggingface.co/Weyaxi/Einstein-7B

output.safetensors

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+oid sha256:62e8c4c1d51a0d5e1cea3fcb6bae530a9aa2d1ac52388128fabb9ecc5e0d1d39
+size 4733750780

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