M4-ai
/

Orca-2.0-Tau-1.8B

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 ---
 library_name: transformers
-tags: []
 ---
-# Model Card for Model ID
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 ## Model Details
@@ -15,51 +37,18 @@ tags: []
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-This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
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@@ -67,133 +56,31 @@ This is the model card of a 🤗 transformers model that has been pushed on the
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 ---
 library_name: transformers
+license: other
+datasets:
+- Open-Orca/SlimOrca
+- m-a-p/Code-Feedback
+- MaziyarPanahi/WizardLM_evol_instruct_V2_196k
+- camel-ai/math
+- camel-ai/physics
+- camel-ai/biology
+- camel-ai/chemistry
+- LDJnr/Capybara
+- jondurbin/airoboros-3.2
+- microsoft/orca-math-word-problems-200k
+language:
+- en
+inference:
+  parameters:
+    do_sample: true
+    temperature: 0.8
+    top_p: 0.95
+    top_k: 40
+    min_p: 0.8
+    max_new_tokens: 250
+    repetition_penalty: 1.1
 ---
+# Hercules-Mini-1.8B
 <!-- Provide a quick summary of what the model is/does. -->
+We fine-tuned tau-1.8B on a high quality mix for general-purpose assistants. A DPO version of this will be released soon.
 ## Model Details
 <!-- Provide a longer summary of what this model is. -->
+This model has capabilities in math, coding, writing, and more. We fine-tuned it using a high quality mix for general-purpose assistants.
+- **Developed by:** M4-ai
+- **Language(s) (NLP):** English and maybe Chinese
+- **License:** tongyi-qianwen license
+- **Finetuned from model:** [tau-1.8B](https://huggingface.co/M4-ai/tau-1.8B)
 ## Uses
 <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+General purpose assistant, question answering, chain-of-thought, etc..
 ### Recommendations
 Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+## Evaluation
+Coming soon
 ## Training Details
 ### Training Data
+- Open-Orca/SlimOrca
+- m-a-p/Code-Feedback
+- MaziyarPanahi/WizardLM_evol_instruct_V2_196k
+- camel-ai/math
+- camel-ai/physics
+- camel-ai/biology
+- camel-ai/chemistry
+- LDJnr/Capybara
+- jondurbin/airoboros-3.2
+- microsoft/orca-math-word-problems-200k
 #### Training Hyperparameters
+- **Training regime:** bf16 non-mixed precision
+## Technical Specifications
 #### Hardware
+We used 8 Kaggle TPUs, and we trained at a global batch size of 128 and sequence length of 2048.