Khasi-English Translation Model (Stage B - Checkpoint 12000)
Fine-tuned facebook/nllb-200-distilled-600M (615M params) for English-Khasi translation.
Training Details
| Detail | Value |
|---|---|
| Base Model | facebook/nllb-200-distilled-600M |
| Task | Machine Translation (English <-> Khasi) |
| Stage | Stage B - Full Silver Training |
| Checkpoint | checkpoint-12000 (Epoch 2.77/3.0) |
| Training Data | 138k parallel pairs |
| GPUs | 2x NVIDIA A100-SXM4-40GB |
Metrics (at checkpoint-12000)
| Metric | Score |
|---|---|
| BLEU | 53.75 |
| chrF | 67.30 |
| Eval Loss | 0.6585 |
Usage
from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
model = AutoModelForSeq2SeqLM.from_pretrained("techno-tuners/khasi-nllb-stage-b-checkpoint-12000")
tokenizer = AutoTokenizer.from_pretrained("techno-tuners/khasi-nllb-stage-b-checkpoint-12000")
tokenizer.src_lang = "eng_Latn"
inputs = tokenizer("Hello, how are you?", return_tensors="pt")
outputs = model.generate(**inputs, forced_bos_token_id=tokenizer.convert_tokens_to_ids("kha_Latn"), max_new_tokens=256)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
Note: This is a training checkpoint, not the final production model.
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