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docs: Update supported models (#389)
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* docs: Update supported models

Signed-off-by: Angel Luu <[email protected]>

* docs: correct some things, add granite MoE

Signed-off-by: Angel Luu <[email protected]>

* docs: remove links for models

Signed-off-by: Angel Luu <[email protected]>

* docs: remove unneed notation

Signed-off-by: Angel Luu <[email protected]>

* docs: new line

Signed-off-by: Angel Luu <[email protected]>

* docs: notation

Signed-off-by: Angel Luu <[email protected]>

* docs: update supported granite 3.0 models

Signed-off-by: Angel Luu <[email protected]>

* docs: update supported granite 3.0 models

Signed-off-by: Angel Luu <[email protected]>

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Signed-off-by: Angel Luu <[email protected]>
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Expand Up @@ -132,7 +132,47 @@ Example: Train.jsonl

## Supported Models

Current supported and tested models are `Llama3` (8B configuration has been tested) and `GPTBigCode`.
- For each tuning technique, we run testing on a single large model of each architecture type and claim support for the smaller models. For example, with QLoRA technique, we tested on granite-34b GPTBigCode and claim support for granite-20b-multilingual.

- LoRA Layers supported : All the linear layers of a model + output `lm_head` layer. Users can specify layers as a list or use `all-linear` as a shortcut. Layers are specific to a model architecture and can be specified as noted [here](https://github.com/foundation-model-stack/fms-hf-tuning?tab=readme-ov-file#lora-tuning-example)

- Legend:

✅ Ready and available

✔️ Ready and available - compatible architecture (*see first bullet point above)

🚫 Not supported

? May be supported, but not tested

Model Name & Size | Model Architecture | Full Finetuning | Low Rank Adaptation (i.e. LoRA) | qLoRA(quantized LoRA) |
-------------------- | ---------------- | --------------- | ------------------------------- | --------------------- |
Granite PowerLM 3B | GraniteForCausalLM | ✅* | ✅* | ✅* |
Granite 3.0 2B | GraniteForCausalLM | ✔️* | ✔️* | ✔️* |
Granite 3.0 8B | GraniteForCausalLM | ✅* | ✅* | ✔️ |
GraniteMoE 1B | GraniteMoeForCausalLM | ✅ | ✅** | ? |
GraniteMoE 3B | GraniteMoeForCausalLM | ✅ | ✅** | ? |
Granite 3B | LlamawithCausalLM | ✅ | ✔️ | ✔️ |
Granite 8B | LlamawithCausalLM | ✅ | ✅ | ✅ |
Granite 13B | GPTBigCodeForCausalLM | ✅ | ✅ | ✔️ |
Granite 20B | GPTBigCodeForCausalLM | ✅ | ✔️ | ✔️ |
Granite 34B | GPTBigCodeForCausalLM | 🚫 | ✅ | ✅ |
Llama3.1-8B | LLaMA 3.1 | ✅*** | ✔️ | ✔️ |  
Llama3.1-70B(same architecture as llama3) | LLaMA 3.1 | 🚫 - same as Llama3-70B | ✔️ | ✔️ |
Llama3.1-405B | LLaMA 3.1 | 🚫 | 🚫 | ✅ |
Llama3-8B | LLaMA 3 | ✅ | ✅ | ✔️ |  
Llama3-70B | LLaMA 3 | 🚫 | ✅ | ✅ |
aLLaM-13b | LlamaForCausalLM |  ✅ | ✅ | ✅ |
Mixtral 8x7B | Mixtral | ✅ | ✅ | ✅ |
Mistral-7b | Mistral | ✅ | ✅ | ✅ |  
Mistral large | Mistral | 🚫 | 🚫 | 🚫 |

(*) - Supported with `fms-hf-tuning` v2.0.1 or later

(**) - Supported for q,k,v,o layers . `all-linear` target modules does not infer on vLLM yet.

(***) - Supported from platform up to 8k context length - same architecture as llama3-8b

## Training

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