GLM-5.2 is live. #1 throughput on OpenRouter, pay-per-token on FriendliAI. Try it today ➜
Banaxi-Tech
Available on FriendliAI
Run this model inference on single tenant GPU with unmatched speed and reliability at scale.
Run this model inference with full control and performance in your environment.
Model Details
Model Provider
Banaxi-Tech
Model Tree
Input Modalities
Output Modalities
Supported Functionality
BananaMind Completor V1 model code and released weights are provided under the Apache License 2.0. See LICENSE.
The training dataset has separate upstream terms. The original ODC-BY 1.0 license text for agentlans/high-quality-english-sentences is included at THIRD_PARTY_LICENSES/ODC-BY-1.0.txt, with attribution in NOTICE.
GPT2LMHeadModelautocomplete_model_gpt2_best.ptmodel.safetensorsThis model was trained on agentlans/high-quality-english-sentences, using the train split for training and the test split for validation.
Dataset attribution: agentlans/high-quality-english-sentences.
Dataset license: ODC-BY 1.0. Follow the dataset license terms when reusing the training data or distributing derived artifacts that require attribution. This release includes the original ODC-BY 1.0 license text in THIRD_PARTY_LICENSES/ODC-BY-1.0.txt.
The released checkpoint is the best validation checkpoint from local GPT-2 training:
| Metric | Value |
|---|---|
| Training step | 70000 |
| Training loss | 1.193311095237732 |
| Validation loss | 1.1782804751396179 |
| Best validation loss | 1.1782804751396179 |
Install dependencies:
bash
pip install -r requirements.txt
Load the model with Transformers:
python
from transformers import AutoModelForCausalLMmodel = AutoModelForCausalLM.from_pretrained(".")
Because this model uses raw byte ids, encode text manually:
python
import torchfrom transformers import AutoModelForCausalLMmodel = AutoModelForCausalLM.from_pretrained(".")model.eval()text = "The weather is beau"tokens = list(text.encode("utf-8"))for _ in range(20):x = torch.tensor([tokens[-128:]], dtype=torch.long)with torch.no_grad():next_id = model(input_ids=x).logits[0, -1].argmax().item()if chr(next_id) in " \n\t.,!?;:":breaktokens.append(next_id)print(bytes(tokens).decode("utf-8", errors="ignore"))
Or use the included helper:
bash
python inference.py "The weather is beau"
model.safetensors: native GPT-2 model weightsconfig.json: Transformers GPT-2 configgeneration_config.json: Transformers generation configinference.py: byte-level autocomplete helpertraining_metadata.json: checkpoint, dataset, and evaluation metadatarequirements.txt: minimal Python dependenciesLICENSE: Apache License 2.0 for this model releaseNOTICE: upstream dataset attribution noticeThis is a small autocomplete model trained for short English sentence contexts. It is not instruction-tuned, not a general chat model, and may produce incomplete, repetitive, or low-quality completions outside short autocomplete-style prompts.
THIRD_PARTY_LICENSES/ODC-BY-1.0.txt