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RichardErkhov/ValiantLabs_-_Llama3.1-8B-Enigma-gguf
ValiantLabs_-_Llama3.1-8B-Enigma-gguf is a machine learning model from RichardErkhov. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
Downloads · 30 days
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From the Hugging Face model README
Quantization made by Richard Erkhov.
Llama3.1-8B-Enigma - GGUF
| Name | Quant method | Size |
|---|---|---|
| Llama3.1-8B-Enigma.Q2_K.gguf | Q2_K | 2.96GB |
| Llama3.1-8B-Enigma.IQ3_XS.gguf | IQ3_XS | 3.28GB |
| Llama3.1-8B-Enigma.IQ3_S.gguf | IQ3_S | 3.43GB |
| Llama3.1-8B-Enigma.Q3_K_S.gguf | Q3_K_S | 3.41GB |
| Llama3.1-8B-Enigma.IQ3_M.gguf | IQ3_M | 3.52GB |
| Llama3.1-8B-Enigma.Q3_K.gguf | Q3_K | 3.74GB |
| Llama3.1-8B-Enigma.Q3_K_M.gguf | Q3_K_M | 3.74GB |
| Llama3.1-8B-Enigma.Q3_K_L.gguf | Q3_K_L | 4.03GB |
| Llama3.1-8B-Enigma.IQ4_XS.gguf | IQ4_XS | 4.18GB |
| Llama3.1-8B-Enigma.Q4_0.gguf | Q4_0 | 4.34GB |
| Llama3.1-8B-Enigma.IQ4_NL.gguf | IQ4_NL | 4.38GB |
| Llama3.1-8B-Enigma.Q4_K_S.gguf | Q4_K_S | 4.37GB |
| Llama3.1-8B-Enigma.Q4_K.gguf | Q4_K | 4.58GB |
| Llama3.1-8B-Enigma.Q4_K_M.gguf | Q4_K_M | 4.58GB |
| Llama3.1-8B-Enigma.Q4_1.gguf | Q4_1 | 4.78GB |
| Llama3.1-8B-Enigma.Q5_0.gguf | Q5_0 | 5.21GB |
| Llama3.1-8B-Enigma.Q5_K_S.gguf | Q5_K_S | 5.21GB |
| Llama3.1-8B-Enigma.Q5_K.gguf | Q5_K | 5.34GB |
| Llama3.1-8B-Enigma.Q5_K_M.gguf | Q5_K_M | 5.34GB |
| Llama3.1-8B-Enigma.Q5_1.gguf | Q5_1 | 5.65GB |
| Llama3.1-8B-Enigma.Q6_K.gguf | Q6_K | 6.14GB |
| Llama3.1-8B-Enigma.Q8_0.gguf | Q8_0 | 7.95GB |
language:
Enigma is a code-instruct model built on Llama 3.1 8b.
This is the 2024-08-10 release of Enigma for Llama 3.1 8b.
Help us and recommend Enigma to your friends! We're excited for more Enigma releases in the future.
Right now, we're working on more new Build Tools to come very soon, built on Llama 3.1 :)
Enigma uses the Llama 3.1 Instruct prompt format. The example script below can be used as a starting point for general chat:
python``` import transformers import torch
model_id = "ValiantLabs/Llama3.1-8B-Enigma"
pipeline = transformers.pipeline( "text-generation", model=model_id, model_kwargs={"torch_dtype": torch.bfloat16}, device_map="auto", )
messages = [ {"role": "system", "content": "You are Enigma, a highly capable code assistant."}, {"role": "user", "content": "Can you explain virtualization to me?"} ]
outputs = pipeline( messages, max_new_tokens=1024, )
print(outputs[0]["generated_text"][-1])
## The Model
Enigma is built on top of Llama 3.1 8b Instruct, using code-instruct data to supplement code-instruct performance using Llama 3.1 Instruct prompt style.
Our current version of the Enigma code-instruct dataset is [sequelbox/Tachibana](https://huggingface.co/datasets/sequelbox/Tachibana), supplemented with a small selection of data from [LDJnr/Pure-Dove](https://huggingface.co/datasets/LDJnr/Pure-Dove) for general chat consistency.

Enigma is created by [Valiant Labs.](http://valiantlabs.ca/)
[Check out our HuggingFace page for Shining Valiant 2 and our other Build Tools models for creators!](https://huggingface.co/ValiantLabs)
[Follow us on X for updates on our models!](https://twitter.com/valiant_labs)
We care about open source.
For everyone to use.
We encourage others to finetune further from our models.