Instructions to use JSALT2026-Conv-AI-Simulator/personaplex-fisher-bc-head with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use JSALT2026-Conv-AI-Simulator/personaplex-fisher-bc-head with PEFT:
Task type is invalid.
- Moshi
How to use JSALT2026-Conv-AI-Simulator/personaplex-fisher-bc-head with Moshi:
# pip install moshi # Run the interactive web server python -m moshi.server --hf-repo "JSALT2026-Conv-AI-Simulator/personaplex-fisher-bc-head" # Then open https://localhost:8998 in your browser
# pip install moshi import torch from moshi.models import loaders # Load checkpoint info from HuggingFace checkpoint = loaders.CheckpointInfo.from_hf_repo("JSALT2026-Conv-AI-Simulator/personaplex-fisher-bc-head") # Load the Mimi audio codec mimi = checkpoint.get_mimi(device="cuda") mimi.set_num_codebooks(8) # Encode audio (24kHz, mono) wav = torch.randn(1, 1, 24000 * 10) # [batch, channels, samples] with torch.no_grad(): codes = mimi.encode(wav.cuda()) decoded = mimi.decode(codes) - Notebooks
- Google Colab
- Kaggle
Add files using upload-large-folder tool
Browse files- adapter_config.json +54 -0
- adapter_model.safetensors +3 -0
- tokenizer.json +0 -0
- tokenizer_config.json +17 -0
adapter_config.json
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{
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"alora_invocation_tokens": null,
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"alpha_pattern": {},
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"arrow_config": null,
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"auto_mapping": {
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"base_model_class": "MoshiForConditionalGeneration",
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"parent_library": "transformers_moshi.modeling_moshi"
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},
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"base_model_name_or_path": "/nas/models/nlu/ppolak/jsalt26/work/personaplex-7b-v1-hf",
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"bias": "none",
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"corda_config": null,
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"ensure_weight_tying": false,
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"eva_config": null,
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"exclude_modules": null,
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"fan_in_fan_out": false,
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"inference_mode": true,
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"init_lora_weights": true,
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"layer_replication": null,
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"layers_pattern": null,
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"layers_to_transform": null,
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"loftq_config": {},
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"lora_alpha": 32,
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"lora_bias": false,
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"lora_dropout": 0.05,
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"lora_ga_config": null,
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"megatron_config": null,
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"megatron_core": "megatron.core",
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"modules_to_save": [
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"backchannel_head"
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],
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"monteclora_config": null,
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"peft_type": "LORA",
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"peft_version": "0.20.0",
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"qalora_group_size": 16,
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"r": 16,
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"rank_pattern": {},
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"revision": null,
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"target_modules": "^decoder\\.model\\.layers\\.\\d+\\.(self_attn\\.(q_proj|k_proj|v_proj|o_proj)\\.linear)$",
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"target_parameters": null,
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"task_type": null,
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"trainable_token_indices": {
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"decoder.model.embed_tokens": [
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4
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],
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"depth_decoder.text_embed_tokens": [
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4
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]
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},
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"use_bdlora": null,
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"use_dora": false,
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"use_qalora": false,
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"use_rslora": false,
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"velora_config": null
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}
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adapter_model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:d58486ca9c2ced82d709d1da1bd6c849442702a693ce1455b534a97af5a44cdc
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size 35702106
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tokenizer.json
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tokenizer_config.json
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{
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"backend": "tokenizers",
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"bos_token": "<s>",
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"chat_template": null,
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"clean_up_tokenization_spaces": false,
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"eos_token": "</s>",
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"is_local": true,
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"local_files_only": false,
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"model_input_names": [
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"input_ids",
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"attention_mask"
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],
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"model_max_length": 1000000000000000019884624838656,
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"pad_token": "<pad>",
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"tokenizer_class": "TokenizersBackend",
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"unk_token": "<unk>"
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}
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