Instructions to use sravanthib/model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use sravanthib/model with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-3.2-3B-Instruct") model = PeftModel.from_pretrained(base_model, "sravanthib/model") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 30
Browse files- adapter_config.json +4 -4
- adapter_model.safetensors +1 -1
- tokenizer.json +2 -2
- training_args.bin +1 -1
adapter_config.json
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"revision": null,
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"target_modules": [
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"q_proj",
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"o_proj",
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"down_proj",
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"up_proj",
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"gate_proj",
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"k_proj",
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"
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],
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"task_type": "CAUSAL_LM",
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"use_dora": false,
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"revision": null,
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"target_modules": [
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"q_proj",
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"down_proj",
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"k_proj",
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"o_proj",
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"gate_proj",
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"v_proj",
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"up_proj"
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],
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"task_type": "CAUSAL_LM",
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"use_dora": false,
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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:
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size 24365712
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version https://git-lfs.github.com/spec/v1
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oid sha256:58a75a8e2482a45dbc5831365c66e3ea55dbbb667bb9e69cc9fd36f46b098342
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size 24365712
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tokenizer.json
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"version": "1.0",
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"truncation": {
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"direction": "Right",
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"max_length":
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"strategy": "LongestFirst",
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"stride": 0
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},
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"padding": {
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"strategy": {
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"Fixed":
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},
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"direction": "Right",
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"pad_to_multiple_of": null,
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"version": "1.0",
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"truncation": {
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"direction": "Right",
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"max_length": 2048,
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"strategy": "LongestFirst",
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"stride": 0
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},
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"padding": {
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"strategy": {
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"Fixed": 2048
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},
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"direction": "Right",
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"pad_to_multiple_of": null,
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training_args.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size 9336
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version https://git-lfs.github.com/spec/v1
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oid sha256:0e24c0f62e07e9288dff962ea7335113da8caeca39e62dcd80c639fa92cfde96
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size 9336
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