gguf endpoints_compatible region:us conversational
---
{}
---
Quantization made by Richard Erkhov.

[Github](https://github.com/RichardErkhov)

[Discord](https://discord.gg/pvy7H8DZMG)

[Request more models](https://github.com/RichardErkhov/quant_request)


Orca-2.0-Tau-1.8B - GGUF
- Model creator: https://huggingface.co/M4-ai/
- Original model: https://huggingface.co/M4-ai/Orca-2.0-Tau-1.8B/


| Name | Quant method | Size |
| ---- | ---- | ---- |
| [Orca-2.0-Tau-1.8B.Q2_K.gguf](https://huggingface.co/RichardErkhov/M4-ai_-_Orca-2.0-Tau-1.8B-gguf/blob/main/Orca-2.0-Tau-1.8B.Q2_K.gguf) | Q2_K | 0.79GB |
| [Orca-2.0-Tau-1.8B.Q3_K_S.gguf](https://huggingface.co/RichardErkhov/M4-ai_-_Orca-2.0-Tau-1.8B-gguf/blob/main/Orca-2.0-Tau-1.8B.Q3_K_S.gguf) | Q3_K_S | 0.89GB |
| [Orca-2.0-Tau-1.8B.Q3_K.gguf](https://huggingface.co/RichardErkhov/M4-ai_-_Orca-2.0-Tau-1.8B-gguf/blob/main/Orca-2.0-Tau-1.8B.Q3_K.gguf) | Q3_K | 0.95GB |
| [Orca-2.0-Tau-1.8B.Q3_K_M.gguf](https://huggingface.co/RichardErkhov/M4-ai_-_Orca-2.0-Tau-1.8B-gguf/blob/main/Orca-2.0-Tau-1.8B.Q3_K_M.gguf) | Q3_K_M | 0.95GB |
| [Orca-2.0-Tau-1.8B.Q3_K_L.gguf](https://huggingface.co/RichardErkhov/M4-ai_-_Orca-2.0-Tau-1.8B-gguf/blob/main/Orca-2.0-Tau-1.8B.Q3_K_L.gguf) | Q3_K_L | 0.98GB |
| [Orca-2.0-Tau-1.8B.IQ4_XS.gguf](https://huggingface.co/RichardErkhov/M4-ai_-_Orca-2.0-Tau-1.8B-gguf/blob/main/Orca-2.0-Tau-1.8B.IQ4_XS.gguf) | IQ4_XS | 1.01GB |
| [Orca-2.0-Tau-1.8B.Q4_0.gguf](https://huggingface.co/RichardErkhov/M4-ai_-_Orca-2.0-Tau-1.8B-gguf/blob/main/Orca-2.0-Tau-1.8B.Q4_0.gguf) | Q4_0 | 1.04GB |
| [Orca-2.0-Tau-1.8B.IQ4_NL.gguf](https://huggingface.co/RichardErkhov/M4-ai_-_Orca-2.0-Tau-1.8B-gguf/blob/main/Orca-2.0-Tau-1.8B.IQ4_NL.gguf) | IQ4_NL | 1.05GB |
| [Orca-2.0-Tau-1.8B.Q4_K_S.gguf](https://huggingface.co/RichardErkhov/M4-ai_-_Orca-2.0-Tau-1.8B-gguf/blob/main/Orca-2.0-Tau-1.8B.Q4_K_S.gguf) | Q4_K_S | 1.08GB |
| [Orca-2.0-Tau-1.8B.Q4_K.gguf](https://huggingface.co/RichardErkhov/M4-ai_-_Orca-2.0-Tau-1.8B-gguf/blob/main/Orca-2.0-Tau-1.8B.Q4_K.gguf) | Q4_K | 1.13GB |
| [Orca-2.0-Tau-1.8B.Q4_K_M.gguf](https://huggingface.co/RichardErkhov/M4-ai_-_Orca-2.0-Tau-1.8B-gguf/blob/main/Orca-2.0-Tau-1.8B.Q4_K_M.gguf) | Q4_K_M | 1.13GB |
| [Orca-2.0-Tau-1.8B.Q4_1.gguf](https://huggingface.co/RichardErkhov/M4-ai_-_Orca-2.0-Tau-1.8B-gguf/blob/main/Orca-2.0-Tau-1.8B.Q4_1.gguf) | Q4_1 | 1.13GB |
| [Orca-2.0-Tau-1.8B.Q5_0.gguf](https://huggingface.co/RichardErkhov/M4-ai_-_Orca-2.0-Tau-1.8B-gguf/blob/main/Orca-2.0-Tau-1.8B.Q5_0.gguf) | Q5_0 | 1.22GB |
| [Orca-2.0-Tau-1.8B.Q5_K_S.gguf](https://huggingface.co/RichardErkhov/M4-ai_-_Orca-2.0-Tau-1.8B-gguf/blob/main/Orca-2.0-Tau-1.8B.Q5_K_S.gguf) | Q5_K_S | 1.24GB |
| [Orca-2.0-Tau-1.8B.Q5_K.gguf](https://huggingface.co/RichardErkhov/M4-ai_-_Orca-2.0-Tau-1.8B-gguf/blob/main/Orca-2.0-Tau-1.8B.Q5_K.gguf) | Q5_K | 1.28GB |
| [Orca-2.0-Tau-1.8B.Q5_K_M.gguf](https://huggingface.co/RichardErkhov/M4-ai_-_Orca-2.0-Tau-1.8B-gguf/blob/main/Orca-2.0-Tau-1.8B.Q5_K_M.gguf) | Q5_K_M | 1.28GB |
| [Orca-2.0-Tau-1.8B.Q5_1.gguf](https://huggingface.co/RichardErkhov/M4-ai_-_Orca-2.0-Tau-1.8B-gguf/blob/main/Orca-2.0-Tau-1.8B.Q5_1.gguf) | Q5_1 | 1.31GB |
| [Orca-2.0-Tau-1.8B.Q6_K.gguf](https://huggingface.co/RichardErkhov/M4-ai_-_Orca-2.0-Tau-1.8B-gguf/blob/main/Orca-2.0-Tau-1.8B.Q6_K.gguf) | Q6_K | 1.47GB |
| [Orca-2.0-Tau-1.8B.Q8_0.gguf](https://huggingface.co/RichardErkhov/M4-ai_-_Orca-2.0-Tau-1.8B-gguf/blob/main/Orca-2.0-Tau-1.8B.Q8_0.gguf) | Q8_0 | 1.82GB |




Original model description:
---
language:
- en
license: other
library_name: transformers
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
inference:
  parameters:
    do_sample: true
    temperature: 0.8
    top_p: 0.95
    top_k: 40
    max_new_tokens: 250
    repetition_penalty: 1.1
model-index:
- name: Orca-2.0-Tau-1.8B
  results:
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: AI2 Reasoning Challenge (25-Shot)
      type: ai2_arc
      config: ARC-Challenge
      split: test
      args:
        num_few_shot: 25
    metrics:
    - type: acc_norm
      value: 37.12
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=M4-ai/Orca-2.0-Tau-1.8B
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: HellaSwag (10-Shot)
      type: hellaswag
      split: validation
      args:
        num_few_shot: 10
    metrics:
    - type: acc_norm
      value: 61.13
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=M4-ai/Orca-2.0-Tau-1.8B
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: MMLU (5-Shot)
      type: cais/mmlu
      config: all
      split: test
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 45.27
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=M4-ai/Orca-2.0-Tau-1.8B
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: TruthfulQA (0-shot)
      type: truthful_qa
      config: multiple_choice
      split: validation
      args:
        num_few_shot: 0
    metrics:
    - type: mc2
      value: 39.1
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=M4-ai/Orca-2.0-Tau-1.8B
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: Winogrande (5-shot)
      type: winogrande
      config: winogrande_xl
      split: validation
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 59.59
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=M4-ai/Orca-2.0-Tau-1.8B
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: GSM8k (5-shot)
      type: gsm8k
      config: main
      split: test
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 28.96
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=M4-ai/Orca-2.0-Tau-1.8B
      name: Open LLM Leaderboard
---

# Orca-2.0-Tau-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. We use the ChatML prompt format.


## Model Details

### Model Description

<!-- 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

<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->

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

## Evaluations

|              Tasks              |Version|Filter|n-shot| Metric |Value |   |Stderr|
|---------------------------------|-------|------|-----:|--------|-----:|---|-----:|
|agieval_nous                     |N/A    |none  |     0|acc     |0.2537|±  |0.0086|
|                                 |       |none  |     0|acc_norm|0.2474|±  |0.0085|
| - agieval_aqua_rat              |      1|none  |     0|acc     |0.2283|±  |0.0264|
|                                 |       |none  |     0|acc_norm|0.2441|±  |0.0270|
| - agieval_logiqa_en             |      1|none  |     0|acc     |0.2750|±  |0.0175|
|                                 |       |none  |     0|acc_norm|0.3164|±  |0.0182|
| - agieval_lsat_ar               |      1|none  |     0|acc     |0.2087|±  |0.0269|
|                                 |       |none  |     0|acc_norm|0.1739|±  |0.0250|
| - agieval_lsat_lr               |      1|none  |     0|acc     |0.1843|±  |0.0172|
|                                 |       |none  |     0|acc_norm|0.2353|±  |0.0188|
| - agieval_lsat_rc               |      1|none  |     0|acc     |0.2602|±  |0.0268|
|                                 |       |none  |     0|acc_norm|0.1784|±  |0.0234|
| - agieval_sat_en                |      1|none  |     0|acc     |0.3544|±  |0.0334|
|                                 |       |none  |     0|acc_norm|0.2961|±  |0.0319|
| - agieval_sat_en_without_passage|      1|none  |     0|acc     |0.3107|±  |0.0323|
|                                 |       |none  |     0|acc_norm|0.2282|±  |0.0293|
| - agieval_sat_math              |      1|none  |     0|acc     |0.2727|±  |0.0301|
|                                 |       |none  |     0|acc_norm|0.2091|±  |0.0275|
|truthfulqa_mc2                   |      2|none  |     0|acc     |0.3923|±  |0.0139|

#### 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.
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_M4-ai__Orca-2.0-Tau-1.8B)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |45.20|
|AI2 Reasoning Challenge (25-Shot)|37.12|
|HellaSwag (10-Shot)              |61.13|
|MMLU (5-Shot)                    |45.27|
|TruthfulQA (0-shot)              |39.10|
|Winogrande (5-shot)              |59.59|
|GSM8k (5-shot)                   |28.96|



