|
--- |
|
language: |
|
- en |
|
pipeline_tag: text-generation |
|
tags: |
|
- cobalt |
|
- valiant |
|
- valiant-labs |
|
- llama |
|
- llama-3.1 |
|
- llama-3.1-instruct |
|
- llama-3.1-instruct-8b |
|
- llama-3 |
|
- llama-3-instruct |
|
- llama-3-instruct-8b |
|
- 8b |
|
- math |
|
- math-instruct |
|
- conversational |
|
- chat |
|
- instruct |
|
model_type: llama |
|
base_model: meta-llama/Meta-Llama-3.1-8B-Instruct |
|
datasets: |
|
- sequelbox/Polytope |
|
- LDJnr/Pure-Dove |
|
license: llama3 |
|
--- |
|
|
|
## Description |
|
This repo contains GGUF format model files for Llama3.1-8B-Cobalt. |
|
|
|
## Files Provided |
|
| Name | Quant | Bits | File Size | Remark | |
|
| ---------------------------- | ----- | ---- | --------- | -------------------------------- | |
|
| llama3.1-8b-cobalt.Q2_K.gguf | Q2_K | 2 | 3.18 GB | 2.96G, +3.5199 ppl @ Llama-3-8B | |
|
| llama3.1-8b-cobalt.Q3_K.gguf | Q3_K | 3 | 4.02 GB | 3.74G, +0.6569 ppl @ Llama-3-8B | |
|
| llama3.1-8b-cobalt.Q4_0.gguf | Q4_0 | 4 | 4.66 GB | 4.34G, +0.4685 ppl @ Llama-3-8B | |
|
| llama3.1-8b-cobalt.Q4_K.gguf | Q4_K | 4 | 4.92 GB | 4.58G, +0.1754 ppl @ Llama-3-8B | |
|
| llama3.1-8b-cobalt.Q5_K.gguf | Q5_K | 5 | 5.73 GB | 5.33G, +0.0569 ppl @ Llama-3-8B | |
|
| llama3.1-8b-cobalt.Q6_K.gguf | Q6_K | 6 | 6.60 GB | 6.14G, +0.0217 ppl @ Llama-3-8B | |
|
| llama3.1-8b-cobalt.Q8_0.gguf | Q8_0 | 8 | 8.54 GB | 7.96G, +0.0026 ppl @ Llama-3-8B | |
|
|
|
## Parameters |
|
| path | type | architecture | rope_theta | sliding_win | max_pos_embed | |
|
| ------------------------------ | ----- | ---------------- | ---------- | ----------- | ------------- | |
|
| ValiantLabs/Llama3.1-8B-Cobalt | llama | LlamaForCausalLM | 500000.0 | null | 131072 | |
|
|
|
|
|
# Original Model Card |
|
|
|
Cobalt is a math-instruct model built on Llama 3.1 8b. |
|
- High quality math instruct performance within the Llama 3 Instruct chat format |
|
- Finetuned on synthetic math-instruct data generated with Llama 3.1 405b. [Find the current version of the dataset here!](https://huggingface.co/datasets/sequelbox/Polytope) |
|
|
|
|
|
## Version |
|
|
|
This is the **2024-08-16** release of Cobalt for Llama 3.1 8b. |
|
|
|
Help us and recommend Cobalt to your friends! We're excited for more Cobalt releases in the future. |
|
|
|
Right now, we're working on more new Build Tools to come very soon, built on Llama 3.1 :) |
|
|
|
|
|
## Prompting Guide |
|
Cobalt 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: |
|
|
|
|
|
import transformers |
|
import torch |
|
|
|
model_id = "ValiantLabs/Llama3.1-8B-Cobalt" |
|
|
|
pipeline = transformers.pipeline( |
|
"text-generation", |
|
model=model_id, |
|
model_kwargs={"torch_dtype": torch.bfloat16}, |
|
device_map="auto", |
|
) |
|
|
|
messages = [ |
|
{"role": "system", "content": "You are Cobalt, expert math AI."}, |
|
{"role": "user", "content": "I'm buying a $50 shirt and a $80 pair of pants, both currently at a 25% discount. How much will I pay?"} |
|
] |
|
|
|
outputs = pipeline( |
|
messages, |
|
max_new_tokens=1024, |
|
) |
|
|
|
print(outputs[0]["generated_text"][-1]) |
|
|
|
|
|
## The Model |
|
Cobalt is built on top of Llama 3.1 8b Instruct, using math-instruct data to supplement math-instruct performance using Llama 3.1 Instruct prompt style. |
|
|
|
Our current version of the Cobalt math-instruct dataset is [sequelbox/Polytope](https://huggingface.co/datasets/sequelbox/Polytope), supplemented with a small selection of data from [LDJnr/Pure-Dove](https://huggingface.co/datasets/LDJnr/Pure-Dove) for general chat consistency. |
|
|
|
|
|
![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/63444f2687964b331809eb55/VCJ8Fmefd8cdVhXSSxJiD.jpeg) |
|
|
|
|
|
Cobalt 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. |