1.4 KiB
1.4 KiB
language, license, pipeline_tag, tags, library_name, datasets
| language | license | pipeline_tag | tags | library_name | datasets | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
|
apache-2.0 | text-generation |
|
transformers |
|
Chytrej2-90M-Base
A fully custom pretrained language model built from scratch on the LLaMA architecture trained on FineWeb Edu dataset.
Built by PingVortex Labs.
Model Details
- Parameters: 90M
- Context length: 8,192 tokens
- Language: English only
- Format: Base model
- Architecture: LLaMA
- License: Apache 2.0
Benchmarks
- No benchmarks - at this scale the benchmarks are more random than based on what the model has learned - we got a checkpoint 55k get better arc easy score than the final model.
Usage
from transformers import LlamaForCausalLM, PreTrainedTokenizerFast
model = LlamaForCausalLM.from_pretrained("pvlabs/Chytrej2-90M-Base")
tokenizer = PreTrainedTokenizerFast.from_pretrained("pvlabs/Chytrej2-90M-Base")
prompt = "The capital of France is"
inputs = tokenizer(prompt, return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=100, repetition_penalty=1.3)
print(tokenizer.decode(outputs[0]))
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