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Browse files- LLaMa-65B-GPTQ4bit.safetensors +3 -0
- README.md +47 -0
- config.json +22 -0
- generation_config.json +7 -0
- quantize_config.json +8 -0
- special_tokens_map.json +23 -0
- tokenizer.json +0 -0
- tokenizer.model +3 -0
- tokenizer_config.json +33 -0
LLaMa-65B-GPTQ4bit.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:38adc50b9fef306016f635688d64d287a54b1d36ae5d08a12285e23c3cc11c8b
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size 33471316664
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README.md
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---
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license: other
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inference: false
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tags:
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- GPTQ
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- 3-bit
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- quantized
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---
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# LLaMa 65B 3bit GPTQ
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This is a GPTQ format quantised 3-bit model of LLaMa 65B.
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It is the result of quantising to 3-bit using [GPTQ-for-LLaMa](https://github.com/qwopqwop200/GPTQ-for-LLaMa).
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## How to easily download and use this model in text-generation-webui
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Open the text-generation-webui UI as normal.
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1. Click the **Model tab**.
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2. Under **Download custom model or LoRA**, enter `TheBloke/LLaMa-65B-GPTQ-3bit`.
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3. Click **Download**.
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4. Wait until it says it's finished downloading.
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5. Click the **Refresh** icon next to **Model** in the top left.
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6. In the **Model drop-down**: choose the model you just downloaded, `LLaMa-65B-GPTQ-3bit`.
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7. If you see an error in the bottom right, ignore it - it's temporary.
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8. Fill out the `GPTQ parameters` on the right: `Bits = 3`, `Groupsize = None`, `model_type = Llama`
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9. Click **Save settings for this model** in the top right.
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10. Click **Reload the Model** in the top right.
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11. Once it says it's loaded, click the **Text Generation tab** and enter a prompt!
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## Provided files
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**Compatible file - LLaMa-65B-GPTQ-3bit.safetensors**
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This will work with all versions of GPTQ-for-LLaMa. It has maximum compatibility
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It was created with the `--act-order` parameter to maximise inference quality, and with group_size = None to minmise VRAM requirements.
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* `Wizard-Vicuna-13B-Uncensored-GPTQ-4bit-128g.compat.no-act-order.safetensors`
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* Works with all versions of GPTQ-for-LLaMa code, both Triton and CUDA branches
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* Works with AutoGPTQ.
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* Works with text-generation-webui one-click-installers
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* Parameters: Groupsize = None. act-order.
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* Command used to create the GPTQ:
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```
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python llama.py /workspace/models/huggyllama_llama-65b wikitext2 --wbits 3 --true-sequential --act-order --save_safetensors /workspace/llama-3bit/LLaMa-65B-GPTQ-3bit.safetensors
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```
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config.json
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{
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"architectures": [
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"LlamaForCausalLM"
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],
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"bos_token_id": 1,
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"eos_token_id": 2,
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"hidden_act": "silu",
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"hidden_size": 8192,
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"initializer_range": 0.02,
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"intermediate_size": 22016,
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"max_sequence_length": 2048,
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"model_type": "llama",
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"num_attention_heads": 64,
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"num_hidden_layers": 80,
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"pad_token_id": 0,
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"rms_norm_eps": 1e-05,
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"tie_word_embeddings": false,
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"torch_dtype": "float16",
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"transformers_version": "4.28.0.dev0",
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"use_cache": true,
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"vocab_size": 32000
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}
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generation_config.json
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{
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"_from_model_config": true,
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"bos_token_id": 1,
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"eos_token_id": 2,
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"pad_token_id": 0,
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"transformers_version": "4.28.0.dev0"
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}
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quantize_config.json
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{
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"bits": 3,
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"group_size": -1,
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"damp_percent": 0.01,
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"desc_act": true,
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"sym": true,
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"true_sequential": true
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}
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special_tokens_map.json
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{
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"bos_token": {
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"content": "<s>",
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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"single_word": false
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},
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"eos_token": {
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"content": "</s>",
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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"single_word": false
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},
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"unk_token": {
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"content": "<unk>",
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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"single_word": false
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}
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}
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tokenizer.json
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See raw diff
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tokenizer.model
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version https://git-lfs.github.com/spec/v1
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oid sha256:9e556afd44213b6bd1be2b850ebbbd98f5481437a8021afaf58ee7fb1818d347
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size 499723
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tokenizer_config.json
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{
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"add_bos_token": true,
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"add_eos_token": false,
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"bos_token": {
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"__type": "AddedToken",
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"content": "<s>",
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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"single_word": false
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},
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"clean_up_tokenization_spaces": false,
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"eos_token": {
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"__type": "AddedToken",
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"content": "</s>",
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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"single_word": false
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},
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"model_max_length": 2048,
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"pad_token": null,
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"sp_model_kwargs": {},
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"tokenizer_class": "LlamaTokenizer",
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"unk_token": {
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"__type": "AddedToken",
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"content": "<unk>",
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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"single_word": false
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}
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}
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