Upload MPTForCausalLM
Browse files- README.md +201 -0
- config.json +88 -0
- generation_config.json +5 -0
- model.safetensors +3 -0
README.md
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---
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library_name: transformers
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tags:
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- trl
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- sft
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---
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# Model Card for Model ID
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<!-- Provide a quick summary of what the model is/does. -->
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## Model Details
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### Model Description
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<!-- Provide a longer summary of what this model is. -->
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This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
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- **Developed by:** [More Information Needed]
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- **Funded by [optional]:** [More Information Needed]
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- **Shared by [optional]:** [More Information Needed]
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- **Model type:** [More Information Needed]
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- **Language(s) (NLP):** [More Information Needed]
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- **License:** [More Information Needed]
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- **Finetuned from model [optional]:** [More Information Needed]
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### Model Sources [optional]
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<!-- Provide the basic links for the model. -->
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- **Repository:** [More Information Needed]
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- **Paper [optional]:** [More Information Needed]
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- **Demo [optional]:** [More Information Needed]
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## Uses
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<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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### Direct Use
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<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
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[More Information Needed]
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### Downstream Use [optional]
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<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
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[More Information Needed]
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### Out-of-Scope Use
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<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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[More Information Needed]
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## Bias, Risks, and Limitations
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<!-- This section is meant to convey both technical and sociotechnical limitations. -->
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[More Information Needed]
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### Recommendations
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<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
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## How to Get Started with the Model
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Use the code below to get started with the model.
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[More Information Needed]
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## Training Details
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### Training Data
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<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
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[More Information Needed]
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### Training Procedure
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<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
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#### Preprocessing [optional]
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[More Information Needed]
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#### Training Hyperparameters
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- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
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#### Speeds, Sizes, Times [optional]
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<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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[More Information Needed]
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## Evaluation
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<!-- This section describes the evaluation protocols and provides the results. -->
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### Testing Data, Factors & Metrics
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#### Testing Data
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<!-- This should link to a Dataset Card if possible. -->
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[More Information Needed]
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#### Factors
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<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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[More Information Needed]
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#### Metrics
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<!-- These are the evaluation metrics being used, ideally with a description of why. -->
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[More Information Needed]
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### Results
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[More Information Needed]
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#### Summary
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## Model Examination [optional]
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<!-- Relevant interpretability work for the model goes here -->
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[More Information Needed]
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## Environmental Impact
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<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
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Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
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- **Hardware Type:** [More Information Needed]
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- **Hours used:** [More Information Needed]
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- **Cloud Provider:** [More Information Needed]
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- **Compute Region:** [More Information Needed]
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- **Carbon Emitted:** [More Information Needed]
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## Technical Specifications [optional]
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### Model Architecture and Objective
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[More Information Needed]
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### Compute Infrastructure
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[More Information Needed]
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#### Hardware
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[More Information Needed]
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#### Software
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[More Information Needed]
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## Citation [optional]
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<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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**BibTeX:**
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[More Information Needed]
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**APA:**
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[More Information Needed]
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## Glossary [optional]
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<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
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[More Information Needed]
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## More Information [optional]
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[More Information Needed]
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## Model Card Authors [optional]
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[More Information Needed]
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## Model Card Contact
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[More Information Needed]
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config.json
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{
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"_name_or_path": "vinai/PhoGPT-4B-Chat",
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"architectures": [
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"MPTForCausalLM"
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],
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"attn_config": {
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"alibi": true,
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"alibi_bias_max": 8,
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"attn_impl": "torch",
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"attn_pdrop": 0.0,
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"attn_type": "multihead_attention",
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"attn_uses_sequence_id": false,
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"clip_qkv": null,
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"prefix_lm": false,
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"qk_gn": false,
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"qk_ln": false,
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"rope": false,
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"rope_dail_config": {
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"pos_idx_in_fp32": true,
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"type": "original",
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"xpos_scale_base": 512
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},
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"rope_hf_config": {
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"factor": 1.0,
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"type": "no_scaling"
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},
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"rope_impl": "dail",
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"rope_theta": 10000,
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"sliding_window_size": -1,
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"softmax_scale": null
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},
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"auto_map": {
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"AutoConfig": "vinai/PhoGPT-4B-Chat--configuration_mpt.MPTConfig",
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"AutoModelForCausalLM": "vinai/PhoGPT-4B-Chat--modeling_mpt.MPTForCausalLM"
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},
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"d_model": 3072,
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"emb_pdrop": 0.0,
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"embedding_fraction": 1.0,
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"expansion_ratio": 4,
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"fc_type": "torch",
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"ffn_config": {
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"fc_type": "torch",
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"ffn_type": "mptmlp"
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},
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"init_config": {
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"emb_init_std": null,
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"emb_init_uniform_lim": null,
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"fan_mode": "fan_in",
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"init_div_is_residual": true,
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"init_gain": 0.0,
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"init_nonlinearity": "relu",
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"init_std": null,
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"name": "kaiming_normal_",
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"verbose": 0
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},
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"init_device": "cpu",
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"learned_pos_emb": false,
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"logit_scale": null,
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"max_seq_len": 8192,
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"model_type": "mpt",
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"n_heads": 24,
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"n_layers": 32,
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"no_bias": false,
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"norm_type": "low_precision_layernorm",
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"pretraining_tp": 1,
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"quantization_config": {
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"_load_in_4bit": true,
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"_load_in_8bit": false,
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"bnb_4bit_compute_dtype": "float16",
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"bnb_4bit_quant_storage": "uint8",
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"bnb_4bit_quant_type": "nf4",
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"bnb_4bit_use_double_quant": true,
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"llm_int8_enable_fp32_cpu_offload": false,
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"llm_int8_has_fp16_weight": false,
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"llm_int8_skip_modules": null,
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"llm_int8_threshold": 6.0,
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"load_in_4bit": true,
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"load_in_8bit": false,
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"quant_method": "bitsandbytes"
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},
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"resid_pdrop": 0.0,
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"torch_dtype": "float32",
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"transformers_version": "4.41.2",
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"use_cache": false,
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"use_pad_tok_in_ffn": true,
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"verbose": 0,
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"vocab_size": 20480
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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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"transformers_version": "4.41.2",
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"use_cache": false
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}
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:d5f78b4ae958e78de63c5b19c442a1eacf2277fb4ea56de28c7c22ffd9954cc4
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size 2326125865
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