Upload 10 files

README.md

@@ -6,6 +6,7 @@ tags:
 - C-RLFT
 datasets:
 - openchat/openchat_sharegpt4_dataset
+- kaist-ai/Feedback-Collection
 - imone/OpenOrca_FLAN
 - LDJnr/LessWrong-Amplify-Instruct
 - LDJnr/Pure-Dove
@@ -18,40 +19,67 @@ datasets:
 library_name: transformers
 pipeline_tag: text-generation
 ---
-
-# OpenChat (1210 Version): Advancing Open-source Language Models with Mixed-Quality Data
-
 <div align="center">
   <img src="https://raw.githubusercontent.com/imoneoi/openchat/master/assets/logo_new.png" style="width: 65%">
+  <h1>Advancing Open-source Language Models with Mixed-Quality Data</h1>
 </div>
 
-<p align="center">
-  <a href="https://github.com/imoneoi/openchat">GitHub Repo</a> •
-  <a href="https://openchat.team">Online Demo</a> •
-  <a href="https://discord.gg/pQjnXvNKHY">Discord</a> •
-  <a href="https://twitter.com/imonenext">Twitter</a> •
-  <a href="https://huggingface.co/openchat">Huggingface</a> •
-  <a href="https://arxiv.org/pdf/2309.11235.pdf">Paper</a>
+<p align="center" style="margin-top: 0px;">
+  <a href="https://openchat.team">
+    <img src="https://github.com/alpayariyak/openchat/blob/master/assets/logo_nobg.png?raw=true" alt="OpenChat Logo" style="width:20px; vertical-align: middle; display: inline-block; margin-right: 5px; margin-left: 10px; margin-top: 0px; margin-bottom: 0px;"/>
+    <span class="link-text" style=" margin-right: 5px;">Online Demo</span>
+  </a> |
+  <a href="https://github.com/imoneoi/openchat">
+    <img src="https://camo.githubusercontent.com/4133dc1cd4511d4a292b84ce10e52e4ed92569fb2a8165381c9c47be5edc2796/68747470733a2f2f6564656e742e6769746875622e696f2f537570657254696e7949636f6e732f696d616765732f706e672f6769746875622e706e67" alt="GitHub Logo" style="width:20px; vertical-align: middle; display: inline-block; margin-right: 5px; margin-left: 5px; margin-top: 0px; margin-bottom: 0px;"/>
+    <span class="link-text" style=" margin-right: 5px;">GitHub</span>
+  </a> |
+  <a href="https://arxiv.org/pdf/2309.11235.pdf">
+    <img src="https://github.com/alpayariyak/openchat/blob/master/assets/arxiv-logomark-small-square-border.png?raw=true" alt="ArXiv Logo" style="width:20px; vertical-align: middle; display: inline-block; margin-right: 5px; margin-left: 5px; margin-top: 0px; margin-bottom: 0px;"/>
+    <span class="link-text" style="margin-right: 5px;">Paper</span>
+  </a> |
+  <a href="https://discord.gg/pQjnXvNKHY">
+    <img src="https://cloud.githubusercontent.com/assets/6291467/26705903/96c2d66e-477c-11e7-9f4e-f3c0efe96c9a.png" alt="Discord Logo" style="width:20px; vertical-align: middle; display: inline-block; margin-right: 5px; margin-left: 5px; margin-top: 0px; margin-bottom: 0px;"/>
+    <span class="link-text">Discord</span>
+  </a>
 </p>
 
-**🔥  **
+<hr>
+<div style="background-color: white; padding: 0.7em; border-radius: 0.5em; color: black; display: flex; flex-direction: column; justify-content: center; text-align: center; ont-size: 0.5em;">
+  <a href="https://huggingface.co/openchat/openchat_3.5" style="text-decoration: none; color: black;">
+    <span style="font-size: 1.7em; font-family: 'Helvetica'; letter-spacing: 0.1em; font-weight: bold; color: black;">OPENCHAT</span><span style="font-size: 1.8em; font-family: 'Helvetica'; color: #3c72db; ">3.5</span>
+        <span style="font-size: 0.7em;  font-family: 'Helvetica'; color:  white; vertical-align: top;  background-color:red;  border-radius: 6em; padding: 0.066em 0.4em; letter-spacing: 0.1em; font-weight: bold;">1210</span>
+    <span style="font-size: 0.85em; font-family: 'Helvetica'; color: black;">
+      <br> 🏆 The Overall Best Performing Open Source 7B Model 🏆
+    <br> 🤖 Outperforms <span style="font-weight: bold;">ChatGPT</span> (March) and <span style="font-weight: bold;">Grok-1</span> 🤖
+      <br> 🚀<span style="font-size: 1em; font-family: 'Helvetica'; color: black; font-weight: bold;">15</span>-point improvement in Coding over <span style="font-size: 0.9em;
+      font-family: 'Helvetica'; color: black; font-weight: bold;">OpenChat-3.5🚀</span>
+      <br><br><span style="font-size: 1em; font-family: 'Helvetica'; color: #3c72db; font-weight: bold;">New Features</span>
+      <br> 💡 2 Modes: Coding + Generalist, Mathematical Reasoning 💡
+      <br> 🧑‍⚖️ Experimental support for Evaluator and Feedback capabilities 🧑‍⚖️
+    </span>
+  </a>
+</div>
 
-| Model                       | HumanEval+ |
-|-----------------------------|------------|
-| GPT-3.5 (December 2023)     | 64.6       |
-| **OpenChat 3.5 1210**       | **63.4**   |
-| GPT-3.5 (March 2023)     | 64.6       |
-| OpenHermes 2.5              | 41.5       |
+<div style="display: flex; justify-content: center; align-items: center">
+  <img src="https://github.com/alpayariyak/openchat/blob/master/assets/1210bench.png?raw=true" style="width: 100%; border-radius: 1em">
+</div>
 
-  <div align="center" style="justify-content: center; align-items: center; "'>
-  <img src="https://github.com/alpayariyak/openchat/blob/master/assets/3.5-benchmarks.png?raw=true" style="width: 100%;  border-radius: 0.5em">
-  </div>
+<div>
+<h3> Table of Contents</h3>
+</div>
 
-OpenChat is an innovative library of open-source language models, fine-tuned with [C-RLFT](https://arxiv.org/pdf/2309.11235.pdf) - a strategy inspired by offline reinforcement learning. Our models learn from mixed-quality data without preference labels, delivering exceptional performance on par with ChatGPT, even with a 7B model. Despite our simple approach, we are committed to developing a high-performance, commercially viable, open-source large language model, and we continue to make significant strides toward this vision.
+1. [Usage](#usage)
+2. [Benchmarks](#benchmarks)
+3. [Limitations](#limitations)
+4. [License](#license)
+5. [Dataset Details](#dataset-details)
+6. [Citation](#citation)
+7. [Acknowledgements](#acknowledgements)
 
-[![DOI](https://zenodo.org/badge/645397533.svg)](https://zenodo.org/badge/latestdoi/645397533)
 
-## Usage
+<div align="center">
+<h2> Usage </h2>
+</div>
 
 To use this model, we highly recommend installing the OpenChat package by following the [installation guide](https://github.com/imoneoi/openchat#installation) in our repository and using the OpenChat OpenAI-compatible API server by running the serving command from the table below. The server is optimized for high-throughput deployment using [vLLM](https://github.com/vllm-project/vllm) and can run on a consumer GPU with 24GB RAM. To enable tensor parallelism, append `--tensor-parallel-size N` to the serving command.
 
@@ -59,10 +87,14 @@ Once started, the server listens at `localhost:18888` for requests and is compat
 
 If you want to deploy the server as an online service, you can use `--api-keys sk-KEY1 sk-KEY2 ...` to specify allowed API keys and `--disable-log-requests --disable-log-stats --log-file openchat.log` for logging only to a file. For security purposes, we recommend using an [HTTPS gateway](https://fastapi.tiangolo.com/es/deployment/concepts/#security-https) in front of the server.
 
+| Model             | Size | Context | Weights                                                          | Serving                                                                                                          |
+|-------------------|------|---------|------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------|
+| OpenChat 3.5 1210 | 7B   | 8192    | [Huggingface](https://huggingface.co/openchat/openchat_3.5_1210) | `python -m ochat.serving.openai_api_server --model openchat/openchat_3.5_1210 --engine-use-ray --worker-use-ray` |
+
 <details>
   <summary>Example request (click to expand)</summary>
 
-Default Mode (Chat & Coding)
+💡 **Default Mode (GPT4 Correct)**: Best for coding, chat and general tasks
 
 ```bash
 curl http://localhost:18888/v1/chat/completions \
@@ -73,7 +105,7 @@ curl http://localhost:18888/v1/chat/completions \
   }'
 ```
 
-Mathematical Reasoning Mode
+🧮 **Mathematical Reasoning Mode**: Tailored for solving math problems
 
 ```bash
 curl http://localhost:18888/v1/chat/completions \
@@ -87,25 +119,23 @@ curl http://localhost:18888/v1/chat/completions \
 
 </details>
 
-| Model             | Size | Context | Weights                                                          | Serving                                                                                                          |
-|-------------------|------|---------|------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------|
-| OpenChat 3.5 1210 | 7B   | 8192    | [Huggingface](https://huggingface.co/openchat/openchat_3.5_1210) | `python -m ochat.serving.openai_api_server --model openchat/openchat_3.5_1210 --engine-use-ray --worker-use-ray` |
-
 ### Conversation templates
 
-Default Mode (GPT4 Correct)
+💡 **Default Mode (GPT4 Correct)**: Best for coding, chat and general tasks
 
 ```
 GPT4 Correct User: Hello<|end_of_turn|>GPT4 Correct Assistant: Hi<|end_of_turn|>GPT4 Correct User: How are you today?<|end_of_turn|>GPT4 Correct Assistant:
 ```
 
-Mathematical Reasoning Mode
+🧮 **Mathematical Reasoning Mode**: Tailored for solving math problems
 
 ```
 Math Correct User: 10.3 − 7988.8133=<|end_of_turn|>Math Correct Assistant:
 ```
 
-The default (GPT4 Correct) template is also available as the integrated `tokenizer.chat_template`, 
+⚠️ **Notice:** Remember to set `<|end_of_turn|>` as end of generation token.
+
+The default (GPT4 Correct) template is also available as the integrated `tokenizer.chat_template`,
 which can be used instead of manually specifying the template:
 
 ```python
@@ -118,16 +148,41 @@ tokens = tokenizer.apply_chat_template(messages, add_generation_prompt=True)
 assert tokens == [1, 420, 6316, 28781, 3198, 3123, 1247, 28747, 22557, 32000, 420, 6316, 28781, 3198, 3123, 21631, 28747, 15359, 32000, 420, 6316, 28781, 3198, 3123, 1247, 28747, 1602, 460, 368, 3154, 28804, 32000, 420, 6316, 28781, 3198, 3123, 21631, 28747]
 ```
 
-## Comparison with [X.AI Grok models](https://x.ai/)
-
-|                   | License     | # Param | Average  | MMLU | HumanEval | MATH     | GSM8k    |
-|-------------------|-------------|---------|----------|------|-----------|----------|----------|
-| OpenChat 3.5 1210 | Apache-2.0  | **7B**  | **60.1** | 65.3 | **68.9**  | **28.9** | **77.3** |
-| OpenChat 3.5      | Apache-2.0  | **7B**  | 56.4     | 64.3 | 55.5      | 28.6     | **77.3** |
-| Grok-0            | Proprietary | 33B     | 44.5     | 65.7 | 39.7      | 15.7     | 56.8     |
-| Grok-1            | Proprietary | ???B    | 55.8     | 73   | 63.2      | 23.9     | 62.9     |
+<div align="center">
+<h2> (Experimental) Evaluator / Feedback Capabilities </h2>
+</div>
+We've included evaluator capabilities in this release to advance open-source models as evaluators. You can use `Default Mode (GPT4 Correct)` with the following prompt (same as [Prometheus](https://huggingface.co/datasets/kaist-ai/Feedback-Collection)) to evaluate a response.
 
-## <a id="benchmarks"></a> Benchmarks
+```
+###Task Description:
+An instruction (might include an Input inside it), a response to evaluate, a reference answer that gets a score of 5, and a score rubric representing a evaluation criteria are given.
+1. Write a detailed feedback that assess the quality of the response strictly based on the given score rubric, not evaluating in general.
+2. After writing a feedback, write a score that is an integer between 1 and 5. You should refer to the score rubric.
+3. The output format should look as follows: "Feedback: (write a feedback for criteria) [RESULT] (an integer number between 1 and 5)"
+4. Please do not generate any other opening, closing, and explanations.
+
+###The instruction to evaluate:
+{orig_instruction}
+
+###Response to evaluate:
+{orig_response}
+
+###Reference Answer (Score 5):
+{orig_reference_answer}
+
+###Score Rubrics:
+[{orig_criteria}]
+Score 1: {orig_score1_description}
+Score 2: {orig_score2_description}
+Score 3: {orig_score3_description}
+Score 4: {orig_score4_description}
+Score 5: {orig_score5_description}
+
+###Feedback: 
+```
+<div align="center">
+<h2> Benchmarks </h2>
+</div>
 
 | Model              | # Params | Average  | MT-Bench     | HumanEval       | BBH MC   | AGIEval  | TruthfulQA    | MMLU         | GSM8K        | BBH CoT     |
 |--------------------|----------|----------|--------------|-----------------|----------|----------|---------------|--------------|--------------|-------------|
@@ -139,9 +194,9 @@ assert tokens == [1, 420, 6316, 28781, 3198, 3123, 1247, 28747, 22557, 32000, 42
 | OpenOrca Mistral   | 7B       | 52.7     | 6.86         | 38.4            | 49.4     | 42.9     | 45.9          | 59.3         | 59.1         | 58.1        |
 | Zephyr-β^          | 7B       | 34.6     | 7.34         | 22.0            | 40.6     | 39.0     | 40.8          | 39.8         | 5.1          | 16.0        |
 | Mistral            | 7B       | -        | 6.84         | 30.5            | 39.0     | 38.0     | -             | 60.1         | 52.2         | -           |
-| Open-source SOTA** | 13B-70B  | 61.4     | 7.71         | 73.2            | 49.7     | 41.7     | 62.3          | 63.7         | 82.3         | 41.4        |
-|                    |          |          | WizardLM 70B | WizardCoder 34B | Orca 13B | Orca 13B | Platypus2 70B | WizardLM 70B | MetaMath 70B | Flan-T5 11B |
 
+<details>
+  <summary>Evaluation Details(click to expand)</summary>
 *: ChatGPT (March) results are from [GPT-4 Technical Report](https://arxiv.org/abs/2303.08774), [Chain-of-Thought Hub](https://github.com/FranxYao/chain-of-thought-hub), and our evaluation. Please note that ChatGPT is not a fixed baseline and evolves rapidly over time.
 
 ^: Zephyr-β often fails to follow few-shot CoT instructions, likely because it was aligned with only chat data but not trained on few-shot data.
@@ -149,15 +204,65 @@ assert tokens == [1, 420, 6316, 28781, 3198, 3123, 1247, 28747, 22557, 32000, 42
 **: Mistral and Open-source SOTA results are taken from reported results in instruction-tuned model papers and official repositories.
 
 All models are evaluated in chat mode (e.g. with the respective conversation template applied). All zero-shot benchmarks follow the same setting as in the AGIEval paper and Orca paper. CoT tasks use the same configuration as Chain-of-Thought Hub, HumanEval is evaluated with EvalPlus, and MT-bench is run using FastChat. To reproduce our results, follow the instructions in [our repository](https://github.com/imoneoi/openchat/#benchmarks).
+</details>
+<div>
+<h3>HumanEval+</h3>
+</div>
+
+| Model                       | Size     | HumanEval+ pass@1 |
+|-----------------------------|----------|------------|
+| ChatGPT (December 12, 2023) | -        | 64.6       |
+| WizardCoder-Python-34B-V1.0 | 34B      | 64.6       |
+| **OpenChat 3.5 (Dec 10)**   | **7B**   | **63.4**   |
+| OpenHermes 2.5              | 7B       | 41.5       |
+
+<div>
+<h3>OpenChat-3.5-1210 vs. Grok</h3>
+</div>
+
+|                   | License     | # Param | Average  | MMLU | HumanEval | MATH     | GSM8k    |
+|-------------------|-------------|---------|----------|------|-----------|----------|----------|
+| OpenChat 3.5 1210 | Apache-2.0  | **7B**  | **60.1** | 65.3 | **68.9**  | **28.9** | **77.3** |
+| OpenChat 3.5      | Apache-2.0  | **7B**  | 56.4     | 64.3 | 55.5      | 28.6     | **77.3** |
+| Grok-0            | Proprietary | 33B     | 44.5     | 65.7 | 39.7      | 15.7     | 56.8     |
+| Grok-1            | Proprietary | ???B    | 55.8     | 73   | 63.2      | 23.9     | 62.9     |
+
+*: Grok results are reported by [X.AI](https://x.ai/).
+
+<div align="center">
+<h2> 中文评估结果 / Chinese Evaluations </h2>
+</div>
+
+⚠️ Note that this model was not explicitly trained in Chinese (only < 0.1% of the data is in Chinese). 请注意本模型没有针对性训练中文（中文数据占比小于0.1%）。
 
-## Limitations
+<div>
+<h3>Multi-Level Multi-Discipline Chinese Evaluation Suite (CEVAL)</h3>
+<div>
+
+| Model    | Avg   | STEM  | Social Science | Humanities | Others |
+|----------|-------|-------|----------------|------------|--------|
+| ChatGPT  | 54.4  | 52.9  | 61.8           | 50.9       | 53.6   |
+| OpenChat | 47.29 | 45.22 | 52.49          | 48.52      | 45.08  |
+
+<div>
+<h3>Massive Multitask Language Understanding in Chinese (CMMLU, 5-shot)</h3>
+</div>
+
+| Models   | STEM  | Humanities | SocialSciences | Other | ChinaSpecific | Avg   |
+|----------|-------|------------|----------------|-------|---------------|-------|
+| ChatGPT  | 47.81 | 55.68      | 56.5           | 62.66 | 50.69         | 55.51 |
+| OpenChat | 38.7  | 45.99      | 48.32          | 50.23 | 43.27         | 45.85 |
+
+<div align="center">
+<h2> Limitations </h2>
+</div>
 
 **Foundation Model Limitations**
 Despite its advanced capabilities, OpenChat is still bound by the limitations inherent in its foundation models. These limitations may impact the model's performance in areas such as:
 
- - Complex reasoning
- - Mathematical and arithmetic tasks
- - Programming and coding challenges
+- Complex reasoning
+- Mathematical and arithmetic tasks
+- Programming and coding challenges
 
 **Hallucination of Non-existent Information**
 OpenChat may sometimes generate information that does not exist or is not accurate, also known as "hallucination". Users should be aware of this possibility and verify any critical information obtained from the model.
@@ -165,24 +270,31 @@ OpenChat may sometimes generate information that does not exist or is not accura
 **Safety**
 OpenChat may sometimes generate harmful, hate speech, biased responses, or answer unsafe questions. It's crucial to apply additional AI safety measures in use cases that require safe and moderated responses.
 
-## License
+<div align="center">
+<h2> License </h2>
+</div>
 
 Our OpenChat 3.5 code and models are distributed under the Apache License 2.0.
 
-## Dataset Details
+<div align="center">
+<h2> Dataset Details </h2>
+</div>
 
 OpenChat 3.5 was trained with C-RLFT on a collection of publicly available high-quality instruction data, with a custom processing pipeline. We detail some notable subsets included here:
 
- - [OpenChat ShareGPT](https://huggingface.co/datasets/openchat/openchat_sharegpt4_dataset)
- - [Open-Orca with FLAN answers](https://huggingface.co/datasets/imone/OpenOrca_FLAN)
- - Capybara [1](https://huggingface.co/datasets/LDJnr/Pure-Dove) [2](https://huggingface.co/datasets/LDJnr/Verified-Camel) [3](https://huggingface.co/datasets/LDJnr/LessWrong-Amplify-Instruct)
- - [GOAT](https://huggingface.co/datasets/tiedong/goat)
- - [Glaive](https://huggingface.co/datasets/glaiveai/glaive-code-assistant)
- - [MetaMathQA](https://huggingface.co/datasets/meta-math/MetaMathQA)
- - [MathInstruct](https://huggingface.co/datasets/TIGER-Lab/MathInstruct)
- - [OpenAssistant](https://huggingface.co/datasets/OpenAssistant/oasst_top1_2023-08-25)
+- [OpenChat ShareGPT](https://huggingface.co/datasets/openchat/openchat_sharegpt4_dataset)
+- [Open-Orca with FLAN answers](https://huggingface.co/datasets/imone/OpenOrca_FLAN)
+- [Feedback-Collection](https://huggingface.co/datasets/kaist-ai/Feedback-Collection)
+- Capybara [1](https://huggingface.co/datasets/LDJnr/Pure-Dove) [2](https://huggingface.co/datasets/LDJnr/Verified-Camel) [3](https://huggingface.co/datasets/LDJnr/LessWrong-Amplify-Instruct)
+- [GOAT](https://huggingface.co/datasets/tiedong/goat)
+- [Glaive](https://huggingface.co/datasets/glaiveai/glaive-code-assistant)
+- [MetaMathQA](https://huggingface.co/datasets/meta-math/MetaMathQA)
+- [MathInstruct](https://huggingface.co/datasets/TIGER-Lab/MathInstruct)
+- [OpenAssistant](https://huggingface.co/datasets/OpenAssistant/oasst_top1_2023-08-25)
 
-## Citation
+<div align="center">
+<h2> Citation </h2>
+</div>
 
 ```
 @article{wang2023openchat,
@@ -193,10 +305,12 @@ OpenChat 3.5 was trained with C-RLFT on a collection of publicly available high-
 }
 ```
 
-## Acknowledgements
+<div align="center">
+<h2> Acknowledgments </h2>
+</div>
 
 We extend our heartfelt gratitude to AutoMeta and caesus from Alignment Lab AI, LDJ and Teknium from Nous Research, alpin and TearGosling from Pygmalion AI for their substantial contributions to data collection and model training.
 
 Special thanks go to Changling Liu from GPT Desk Pte. Ltd., Qiying Yu at Tsinghua University, Baochang Ma, and Hao Wan from 01.AI company for their generous provision of resources. We are also deeply grateful to Jianxiong Li and Peng Li at Tsinghua University for their insightful discussions.
 
-Furthermore, we appreciate the developers behind the following projects for their significant contributions to our research: [Mistral](https://mistral.ai/), [Chain-of-Thought Hub](https://github.com/FranxYao/chain-of-thought-hub), [Llama 2](https://ai.meta.com/llama/), [Self-Instruct](https://arxiv.org/abs/2212.10560), [FastChat (Vicuna)](https://github.com/lm-sys/FastChat), [Alpaca](https://github.com/tatsu-lab/stanford_alpaca.git), and [StarCoder](https://github.com/bigcode-project/starcoder). Their work has been instrumental in driving our research forward.
+Furthermore, we appreciate the developers behind the following projects for their significant contributions to our research: [Mistral](https://mistral.ai/), [Chain-of-Thought Hub](https://github.com/FranxYao/chain-of-thought-hub), [Llama 2](https://ai.meta.com/llama/), [Self-Instruct](https://arxiv.org/abs/2212.10560), [FastChat (Vicuna)](https://github.com/lm-sys/FastChat), [Alpaca](https://github.com/tatsu-lab/stanford_alpaca.git), and [StarCoder](https://github.com/bigcode-project/starcoder). Their work has been instrumental in driving our research forward.

config.json

@@ -4,7 +4,7 @@
     "MistralForCausalLM"
   ],
   "bos_token_id": 1,
-  "eos_token_id": 2,
+  "eos_token_id": 32000,
   "hidden_act": "silu",
   "hidden_size": 4096,
   "initializer_range": 0.02,

generation_config.json

@@ -0,0 +1,9 @@
+{
+  "_from_model_config": true,
+  "bos_token_id": 1,
+  "eos_token_id": 32000,
+  "max_length": 8192,
+  "pad_token_id": 0,
+  "temperature": 0.5,
+  "transformers_version": "4.35.2"
+}

huggingface-metadata.txt

@@ -0,0 +1,8 @@
+url: https://huggingface.co/openchat/openchat-3.5-1210
+branch: main
+download date: 2023-12-18 02:14:41
+sha256sum:
+    c65531d6a5a9bb8345aa117528f3f4105b0bf357eab647519c19b4dca952e89b model-00001-of-00003.safetensors
+    26b18d5d207afd2257427cfa2a7f5f041bea575b77113855a25faae88d82c408 model-00002-of-00003.safetensors
+    3ff9fa33b10323cb7604dfa9da1d0fac1af5f2aa485744031b5f43d0d8885563 model-00003-of-00003.safetensors
+    dadfd56d766715c61d2ef780a525ab43b8e6da4de6865bda3d95fdef5e134055 tokenizer.model

special_tokens_map.json

@@ -11,7 +11,7 @@
     "single_word": false
   },
   "eos_token": {
-    "content": "</s>",
+    "content": "<|end_of_turn|>",
     "lstrip": false,
     "normalized": false,
     "rstrip": false,

tokenizer_config.json

@@ -48,8 +48,9 @@
     "<|pad_0|>"
   ],
   "bos_token": "<s>",
+  "chat_template": "{{ bos_token }}{% for message in messages %}{{ 'GPT4 Correct ' + message['role'].title() + ': ' + message['content'] + '<|end_of_turn|>'}}{% endfor %}{% if add_generation_prompt %}{{ 'GPT4 Correct Assistant:' }}{% endif %}",
   "clean_up_tokenization_spaces": false,
-  "eos_token": "</s>",
+  "eos_token": "<|end_of_turn|>",
   "legacy": true,
   "model_max_length": 1000000000000000019884624838656,
   "pad_token": null,