catrex-1.0 / README.md
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Catrex 1.0: weights, tokenizer, chat template
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metadata
license: apache-2.0
library_name: transformers
pipeline_tag: text-generation
language:
  - ru
  - en
tags:
  - catrex
  - llama
  - gguf
  - text-generation
datasets:
  - HuggingFaceFW/fineweb-edu
  - HuggingFaceH4/ultrachat_200k
  - IlyaGusev/saiga_scored
  - d0rj/OpenOrca-ru

Catrex 1.0

Bilingual (RU/EN) chat model on 65M parameters, trained from scratch.

Results

Metric Value
val loss 4.8311
perplexity 125.3
Parameters 64.82M
Context 512 tokens
Training steps 300

Run in LM Studio

  1. Download catrex-1.0-f16.gguf
  2. Put it in ~/.lmstudio/models/Catniti/catrex-1.0/
  3. Load it in LM Studio (chat template is already inside the file)

Run via llama.cpp

llama-cli -hf Catniti/catrex-1.0:f16 -p "Hi!"

Python (transformers)

from transformers import AutoModelForCausalLM, AutoTokenizer
tok = AutoTokenizer.from_pretrained("Catniti/catrex-1.0")
model = AutoModelForCausalLM.from_pretrained("Catniti/catrex-1.0")
msgs = [{"role": "user", "content": "Hi!"}]
ids = tok.apply_chat_template(msgs, add_generation_prompt=True, return_tensors="pt")
out = model.generate(ids, max_new_tokens=100, temperature=0.8, do_sample=True)
print(tok.decode(out[0][ids.shape[1]:], skip_special_tokens=True))

Prompt format

ChatML:

<|im_start|>user
Hi!<|im_end|>
<|im_start|>assistant