Upload README.md with huggingface_hub

README.md

@@ -0,0 +1,144 @@
+
+---
+
+license: apache-2.0
+tags:
+- alignment-handbook
+- generated_from_trainer
+- trl
+- sft
+- generated_from_trainer
+datasets:
+
+- jan-hq/bagel_sft_binarized
+- jan-hq/dolphin_binarized
+- jan-hq/openhermes_binarized
+- jan-hq/bagel_dpo_binarized
+base_model: TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T
+pipeline_tag: text-generation
+inference:
+  parameters:
+    temperature: 0.7
+    max_new_tokens: 40
+widget:
+  - messages:
+      - role: user
+        content: Tell me about NVIDIA in 20 words
+
+---
+
+[![QuantFactory Banner](https://lh7-rt.googleusercontent.com/docsz/AD_4nXeiuCm7c8lEwEJuRey9kiVZsRn2W-b4pWlu3-X534V3YmVuVc2ZL-NXg2RkzSOOS2JXGHutDuyyNAUtdJI65jGTo8jT9Y99tMi4H4MqL44Uc5QKG77B0d6-JfIkZHFaUA71-RtjyYZWVIhqsNZcx8-OMaA?key=xt3VSDoCbmTY7o-cwwOFwQ)](https://hf.co/QuantFactory)
+
+
+# QuantFactory/LlamaCorn-1.1B-Chat-GGUF
+This is quantized version of [jan-hq/LlamaCorn-1.1B-Chat](https://huggingface.co/jan-hq/LlamaCorn-1.1B-Chat) created using llama.cpp
+
+# Original Model Card
+
+
+<!-- header start -->
+<!-- 200823 -->
+
+<div style="width: auto; margin-left: auto; margin-right: auto"
+>
+<img src="https://github.com/janhq/jan/assets/89722390/35daac7d-b895-487c-a6ac-6663daaad78e" alt="Jan banner"
+ style="width: 100%; min-width: 400px; display: block; margin: auto;">
+</div>
+
+<p align="center">
+    <a href="https://jan.ai/">Jan</a
+> 
+    - <a
+ href="https://discord.gg/AsJ8krTT3N">Discord</a>
+</p>
+<!-- header end -->
+
+# Model description
+
+- Finetuned [TinyLlama-1.1B](TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T) further for handling simple tasks and have acceptable conversational quality
+- Utilized high-quality opensource dataset
+- Can be run on [TensorRT-LLM](https://github.com/NVIDIA/TensorRT-LLM) on consumer devices
+- Can fit into laptop dGPUs with as little as >=6gb of VRAM
+
+# Prompt template
+
+ChatML
+```
+<|im_start|>system
+{system_message}<|im_end|>
+<|im_start|>user
+{prompt}<|im_end|>
+<|im_start|>assistant
+
+```
+
+# Run this model
+You can run this model using [Jan Desktop](https://jan.ai/) on Mac, Windows, or Linux.
+
+Jan is an open source, ChatGPT alternative that is:
+
+- 💻  **100% offline on your machine**: Your conversations remain confidential, and visible only to you.
+- 🗂️ **
+An Open File Format**: Conversations and model settings stay on your computer and can be exported or deleted at any time.
+- 🌐 **OpenAI Compatible**: Local server on port `1337` with OpenAI compatible endpoints
+
+- 🌍 **Open Source & Free**: We build in public; check out our [Github](https://github.com/janhq)
+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/65713d70f56f9538679e5a56/r7VmEBLGXpPLTu2MImM7S.png)
+
+
+# About Jan
+Jan believes in the need for an open-source AI ecosystem and is building the infra and tooling to allow open-source AIs to compete on a level playing field with proprietary ones.
+
+Jan's long-term vision is to build a cognitive framework for future robots, who are practical, useful assistants for humans and businesses in everyday life.
+
+# LlamaCorn-1.1B-Chat
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 5e-07
+- train_batch_size: 2
+- eval_batch_size: 4
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 2
+- gradient_accumulation_steps: 16
+- total_train_batch_size: 64
+- total_eval_batch_size: 8
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 3
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
+|:-------------:|:-----:|:-----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
+| 0.9958        | 0.03  | 100   | 1.0003          | -0.0002        | -0.0002          | 0.4930             | -0.0001         | -180.9232      | -195.6078    | -2.6876         | -2.6924       |
+| 0.9299        | 1.02  | 3500  | 0.9439          | -0.1570        | -0.2195          | 0.5770             | 0.0625          | -183.1160      | -197.1755    | -2.6612         | -2.6663       |
+| 0.9328        | 2.01  | 6900  | 0.9313          | -0.2127        | -0.2924          | 0.5884             | 0.0798          | -183.8456      | -197.7321    | -2.6296         | -2.6352       |
+| 0.9321        | 2.98  | 10200 | 0.9305          | -0.2149        | -0.2955          | 0.5824             | 0.0805          | -183.8759      | -197.7545    | -2.6439         | -2.6493       |
+
+
+### Framework versions
+
+- Transformers 4.36.2
+- Pytorch 2.1.2+cu121
+- Datasets 2.14.6
+- Tokenizers 0.15.0
+
+# [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_jan-hq__LlamaCorn-1.1B)
+
+|             Metric              |Value|
+|---------------------------------|----:|
+|Avg.                             |36.94|
+|AI2 Reasoning Challenge (25-Shot)|34.13|
+|HellaSwag (10-Shot)              |59.33|
+|MMLU (5-Shot)                    |29.01|
+|TruthfulQA (0-shot)              |36.78|
+|Winogrande (5-shot)              |61.96|
+|GSM8k (5-shot)                   | 0.45|