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--- |
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language: |
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- en |
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pipeline_tag: text-generation |
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tags: |
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- enigma |
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- valiant |
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- valiant-labs |
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- llama |
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- llama-3.1 |
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- llama-3.1-instruct |
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- llama-3.1-instruct-8b |
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- llama-3 |
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- llama-3-instruct |
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- llama-3-instruct-8b |
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- 8b |
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- code |
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- code-instruct |
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- python |
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- conversational |
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- chat |
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- instruct |
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base_model: meta-llama/Meta-Llama-3.1-8B-Instruct |
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datasets: |
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- sequelbox/Tachibana |
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- sequelbox/Supernova |
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model_type: llama |
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license: llama3.1 |
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--- |
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## Description |
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This repo contains GGUF format model files for Llama3.1-8B-Enigma. |
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## Files Provided |
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| Name | Quant | Bits | File Size | Remark | |
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| ---------------------------- | ----- | ---- | --------- | -------------------------------- | |
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| llama3.1-8b-enigma.Q2_K.gguf | Q2_K | 2 | 3.18 GB | 2.96G, +3.5199 ppl @ Llama-3-8B | |
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| llama3.1-8b-enigma.Q3_K.gguf | Q3_K | 3 | 4.02 GB | 3.74G, +0.6569 ppl @ Llama-3-8B | |
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| llama3.1-8b-enigma.Q4_0.gguf | Q4_0 | 4 | 4.66 GB | 4.34G, +0.4685 ppl @ Llama-3-8B | |
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| llama3.1-8b-enigma.Q4_K.gguf | Q4_K | 4 | 4.92 GB | 4.58G, +0.1754 ppl @ Llama-3-8B | |
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| llama3.1-8b-enigma.Q5_K.gguf | Q5_K | 5 | 5.73 GB | 5.33G, +0.0569 ppl @ Llama-3-8B | |
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| llama3.1-8b-enigma.Q6_K.gguf | Q6_K | 6 | 6.60 GB | 6.14G, +0.0217 ppl @ Llama-3-8B | |
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| llama3.1-8b-enigma.Q8_0.gguf | Q8_0 | 8 | 8.54 GB | 7.96G, +0.0026 ppl @ Llama-3-8B | |
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## Parameters |
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| path | type | architecture | rope_theta | sliding_win | max_pos_embed | |
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| ------------------------------ | ----- | ---------------- | ---------- | ----------- | ------------- | |
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| ValiantLabs/Llama3.1-8B-Enigma | llama | LlamaForCausalLM | 500000.0 | null | 131072 | |
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# Original Model Card |
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![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/64f267a8a4f79a118e0fcc89/it7MY5MyLCLpFQev5dUis.jpeg) |
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Enigma is a code-instruct model built on Llama 3.1 8b. |
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- High quality code instruct performance within the Llama 3 Instruct chat format |
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- Finetuned on synthetic code-instruct data generated with Llama 3.1 405b. [Find the current version of the dataset here!](https://huggingface.co/datasets/sequelbox/Tachibana) |
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- Overall chat performance supplemented with [generalist synthetic data.](https://huggingface.co/datasets/sequelbox/Supernova) |
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## Version |
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This is the **2024-09-04** release of Enigma for Llama 3.1 8b, enhancing code-instruct and general chat capabilities. |
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Help us and recommend Enigma to your friends! We're excited for more Enigma releases in the future. |
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Right now, we're working on more new Build Tools to come very soon, built on Llama 3.1 :) |
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## Prompting Guide |
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Enigma uses the [Llama 3.1 Instruct](https://huggingface.co/meta-llama/Meta-Llama-3.1-8B-Instruct) prompt format. The example script below can be used as a starting point for general chat: |
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```python |
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import transformers |
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import torch |
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model_id = "ValiantLabs/Llama3.1-8B-Enigma" |
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pipeline = transformers.pipeline( |
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"text-generation", |
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model=model_id, |
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model_kwargs={"torch_dtype": torch.bfloat16}, |
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device_map="auto", |
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) |
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messages = [ |
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{"role": "system", "content": "You are Enigma, a highly capable code assistant."}, |
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{"role": "user", "content": "Can you explain virtualization to me?"} |
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] |
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outputs = pipeline( |
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messages, |
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max_new_tokens=1024, |
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) |
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print(outputs[0]["generated_text"][-1]) |
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``` |
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## The Model |
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Enigma is built on top of Llama 3.1 8b Instruct, using high quality code-instruct data and general chat data in Llama 3.1 Instruct prompt style to supplement overall performance. |
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Our current version of Enigma is trained on code-instruct data from [sequelbox/Tachibana](https://huggingface.co/datasets/sequelbox/Tachibana) and general chat data from [sequelbox/Supernova.](https://huggingface.co/datasets/sequelbox/Supernova) |
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![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/63444f2687964b331809eb55/VCJ8Fmefd8cdVhXSSxJiD.jpeg) |
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Enigma is created by [Valiant Labs.](http://valiantlabs.ca/) |
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[Check out our HuggingFace page for Shining Valiant 2 and our other Build Tools models for creators!](https://huggingface.co/ValiantLabs) |
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[Follow us on X for updates on our models!](https://twitter.com/valiant_labs) |
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We care about open source. |
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For everyone to use. |
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We encourage others to finetune further from our models. |