![amber logo](amber_logo.png)
Amber is the first model in the LLM360 family. Amber is an
7B English language model with the LLaMA architecture.
LLM360 is an initiative for comprehensive and fully open-sourced LLMs,
where all training details, model checkpoints, intermediate results, and
additional analyses are made available to the community. Our goal is to advance
the field by inviting the community to deepen the understanding of LLMs
together. As the first step of the project LLM360, we release all intermediate
model checkpoints, our fully-prepared pre-training dataset, all source code and
configurations, and training details. We are
committed to continually pushing the boundaries of LLMs through this open-source
effort.
Get access now at LLM360 site
- Model type: Language model with the same architecture as LLaMA-7B
- Language(s) (NLP): English
- License: Apache 2.0
- Resources for more information:
from transformers import LlamaTokenizer, LlamaForCausalLM
tokenizer = LlamaTokenizer.from_pretrained("LLM360/Amber", revision="ckpt_356")
model = LlamaForCausalLM.from_pretrained("LLM360/Amber", revision="ckpt_356")
input_text = "translate English to German: How old are you?"
input_ids = tokenizer(input_text, return_tensors="pt").input_ids
outputs = model.generate(input_ids)
print(tokenizer.decode(outputs[0]))
Subset |
Tokens (Billion) |
Arxiv |
30.00 |
Book |
28.86 |
C4 |
197.67 |
Refined-Web |
665.01 |
StarCoder |
291.92 |
StackExchange |
21.75 |
Wikipedia |
23.90 |
Total |
1259.13 |
Hyperparameter |
Value |
Total Parameters |
6.7B |
Hidden Size |
4096 |
Intermediate Size (MLPs) |
11008 |
Number of Attention Heads |
32 |
Number of Hidden Lyaers |
32 |
RMSNorm ษ |
1e^-6 |
Max Seq Length |
2048 |
Vocab Size |
32000 |
Training Loss |
![loss curve](amber-training-loss.png) |
ARC |
HellaSwag |
![arc](amber-arc-curve.png) |
![hellaswag](amber-hellaswag-curve.png) |
MMLU |
TruthfulQA |
![mmlu](amber-mmlu-curve.png) |
![truthfulqa](amber-truthfulqa-curve.png) |
Coming soon...