mode card pre 1

README.md

@@ -1,18 +1,73 @@
 ---
+language:
+- en
 license: other
-base_model: meta-llama/Meta-Llama-3-8B
 tags:
 - axolotl
 - generated_from_trainer
-model-index:
-- name: Einstein-v6.1-Llama3-8B
-  results: []
+- instruct
+- finetune
+- chatml
+- gpt4
+- synthetic data
+- science
+- physics
+- chemistry
+- biology
+- math
+- llama
+- llama3
+base_model: meta-llama/Meta-Llama-3-8B
+datasets:
+- allenai/ai2_arc
+- camel-ai/physics
+- camel-ai/chemistry
+- camel-ai/biology
+- camel-ai/math
+- metaeval/reclor
+- openbookqa
+- mandyyyyii/scibench
+- derek-thomas/ScienceQA
+- TIGER-Lab/ScienceEval
+- jondurbin/airoboros-3.2
+- LDJnr/Capybara
+- Cot-Alpaca-GPT4-From-OpenHermes-2.5
+- STEM-AI-mtl/Electrical-engineering
+- knowrohit07/saraswati-stem
+- sablo/oasst2_curated
+- lmsys/lmsys-chat-1m
+- TIGER-Lab/MathInstruct
+- bigbio/med_qa
+- meta-math/MetaMathQA-40K
+- openbookqa
+- piqa
+- metaeval/reclor
+- derek-thomas/ScienceQA
+- scibench
+- sciq
+- Open-Orca/SlimOrca
+- migtissera/Synthia-v1.3
+- TIGER-Lab/ScienceEval
+- allenai/WildChat
+- microsoft/orca-math-word-problems-200k
+- openchat/openchat_sharegpt4_dataset
+- teknium/GPTeacher-General-Instruct
+- m-a-p/CodeFeedback-Filtered-Instruction
+- totally-not-an-llm/EverythingLM-data-V3
+- HuggingFaceH4/no_robots
+- OpenAssistant/oasst_top1_2023-08-25
+- WizardLM/WizardLM_evol_instruct_70k
 ---
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/6468ce47e134d050a58aa89c/5s12oq859qLfDkkTNam_C.png)
 
-<!-- This model card has been generated automatically according to the information the Trainer had access to. You
-should probably proofread and complete it, then remove this comment. -->
+# 🔬 Einstein-v6.1-Llama3-8B
+
+This model is a full fine-tuned version of [meta-llama/Meta-Llama-3-8B](https://huggingface.co/Einstein-v6.1-Llama3-8) on diverse datasets.
+
+This model is finetuned using `8xRTX3090` + `1xRTXA6000` using [axolotl](https://github.com/OpenAccess-AI-Collective/axolotl).
+
+This model's training was sponsored by [sablo.ai](https://sablo.ai). 
 
-[<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>
 
 axolotl version: `0.4.0`
@@ -164,61 +219,73 @@ special_tokens:
   pad_token: <|end_of_text|> # changed
 tokens:
   - "<|im_start|>"
+```
+</details><br>
+
+# 💬 Prompt Template
+
+You can use ChatML prompt template while using the model:
+
+### ChatML
 
+```
+<|im_start|>system
+{system}<|im_end|>
+<|im_start|>user
+{user}<|im_end|>
+<|im_start|>assistant
+{asistant}<|im_end|>
 ```
 
-</details><br>
+This prompt template is available as a [chat template](https://huggingface.co/docs/transformers/main/chat_templating), which means you can format messages using the
+`tokenizer.apply_chat_template()` method:
+
+```python
+messages = [
+    {"role": "system", "content": "You are helpful AI asistant."},
+    {"role": "user", "content": "Hello!"}
+]
+gen_input = tokenizer.apply_chat_template(message, return_tensors="pt")
+model.generate(**gen_input)
+```
+
+# 🔄 Quantizationed versions
 
-# Einstein-v6.1-Llama3-8B
+## GGUF [@bartowski](https://huggingface.co/bartowski)
 
-This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B) on the None dataset.
-It achieves the following results on the evaluation set:
-- Loss: 0.5786
+- https://huggingface.co/bartowski/Einstein-v6.1-Llama3-8B-GGUF
 
-## Model description
+## ExLlamaV2 [@bartowski](https://huggingface.co/bartowski)
 
-More information needed
+- https://huggingface.co/bartowski/Einstein-v6.1-Llama3-8B-exl2
 
-## Intended uses & limitations
+# 🎯 [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
 
-More information needed
 
-## Training and evaluation data
+# 🤖 Additional information about training
 
-More information needed
+This model is full fine-tuned for 2 epoch. 
 
-## Training procedure
+Total number of steps was 2026.
 
-### Training hyperparameters
+<details><summary>Loss graph</summary>
 
-The following hyperparameters were used during training:
-- learning_rate: 5e-06
-- train_batch_size: 1
-- eval_batch_size: 1
-- seed: 42
-- distributed_type: multi-GPU
-- num_devices: 9
-- gradient_accumulation_steps: 4
-- total_train_batch_size: 36
-- total_eval_batch_size: 9
-- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
-- lr_scheduler_type: cosine
-- lr_scheduler_warmup_steps: 10
-- num_epochs: 2
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/6468ce47e134d050a58aa89c/Ycs7ZpoqmxFt0u9rybCO1.png)
 
-### Training results
+</details><br>
 
-| Training Loss | Epoch | Step | Validation Loss |
-|:-------------:|:-----:|:----:|:---------------:|
-| 1.6849        | 0.0   | 1    | 1.7294          |
-| 0.6045        | 0.5   | 507  | 0.6127          |
-| 0.5986        | 1.0   | 1014 | 0.5868          |
-| 0.5136        | 1.48  | 1521 | 0.5786          |
+# 🤝 Acknowledgments
 
+Thanks to [sablo.ai](https://sablo.ai) for sponsoring this model.
+
+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.
+
+Thanks to all open source AI community.
+
+[<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)
 
-### Framework versions
+If you would like to support me:
 
-- Transformers 4.40.0.dev0
-- Pytorch 2.1.2+cu118
-- Datasets 2.18.0
-- Tokenizers 0.15.0
+[☕ Buy Me a Coffee](https://www.buymeacoffee.com/weyaxi)